computing cambridge phd

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PhD in Scientific Computing

• Centre for Doctoral Training in Computational Methods for Materials Science
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Information on how to enter our PhD programme

A common route for admission into our PhD programme is via the Centre’s MPhil programme in Scientific Computing. The MPhil is offered by the University of Cambridge as a full-time course and introduces students to research skills and specialist knowledge. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are formidably well-equipped to proceed to doctoral research or directly into employment in industry.

List of the groups who offer PhD positions in Scientific Computing and its applications

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Cambridge centre for data-driven discovery, currently advertised phd studentships.

• The majority of current PhD studentships are listed on the  University's Jobs site
• For a full list of departments and faculties at the University, visit this page where you can learn more about the research interests within each department
• To find academics you might like to work with, use our directory

Graduate Admissions

The  Graduate Admissions  office provides a range of information on postgraduate programmes at Cambridge, along with a step-by-step guide to the application process. It is advisable to start researching funding opportunities at least a year before your course begins.

MPhil and PhD course relevant to data science - from across University of Cambridge

Please visit the relevant pages and contact the relevant education provider if you have queries. You should pay particular attention to the entry requirements and guidance for applicants there.

MPhil in Machine Learning and Machine Intelligence - an eleven month full-time programme offered by the Machine Learning Group, the Speech Group, and the Computer Vision and Robotics Group in the Cambridge University Department of Engineering.  The course aims to teach the state-of-the-art in machine learning, speech and language processing, and computer vision; to give students the skills and expertise necessary to take leading roles in industry and to equip them with the research skills necessary for doctoral study at Cambridge and other universities.

PhD programme in Advanced Machine Learning - The Machine Learning Group is based in the Department of Engineering, and encourages applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its scientific applications. 

Cambridge Centre for AI in Medicine - Cambridge Centre for AI in Medicine (CCAIM) is a multi-disciplinary centre established by the University of Cambridge in 2020 to develop pioneering AI machine learning (ML) technologies that will transform biomedical science, medicine and healthcare. PhD studentships are oten available, please check their website for details.

SynTech Centre for Doctoral Training - EPSRC Centre for Doctoral Training in Next Generation Synthetic Chemistry Enabled by Digital Molecular Technologies. An interdisciplinary cohort-driven programme to produce the next generation of molecule making scientists by combining Synthetic Chemistry, Chemical Engineering, Engineering, Machine Learning and Artificial Intelligence.

Advanced Computer Science MPhil  - The MPhil in Advanced Computer Science (the ACS) is designed to prepare students for doctoral research, whether at Cambridge or elsewhere. Typical applicants will have undertaken a first degree in computer science or an equivalent subject, and will be expected to be familiar with basic concepts and practices. The ACS is a nine–month course which starts in early October and finishes on 30 June. It covers advanced material in both theoretical and practical areas as well as instilling the elements of research practice.

Application of Artificial Intelligence to the study of Environmental Risks MRes and PhD - The UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) trains researchers (through several multidisciplinary cohorts) to be uniquely equipped to develop and apply leading-edge computational approaches to address critical global environmental challenges by exploiting vast, diverse and often currently untapped environmental data sets. Embedded in the outstanding research environments of the University of Cambridge and the British Antarctic Survey (BAS), the AI4ER CDT addresses problems that are relevant to  building resilience to environmental hazards and managing environmental change .

Postgraduate Study in Mathematics - Various postgraduate courses of a mathematical nature are available at the University of Cambridge, including both taught courses and research degrees.

Mathematics of Information PhD  - This cutting-edge training Centre in the Mathematics of Information produces a new generation of leaders in the theory and practice of modern data science, with an emphasis on the mathematical underpinnings of this new scientific field. The Cambridge Mathematics of Information (CMI) PhD is a four-year course leading to a single PhD thesis.

Cambridge Computational Biology Institute MPhil and PhD ​ - The MPhil in Computational Biology course is aimed at introducing students in the biological, mathematical and physical sciences to quantitative aspects of modern biology and medicine, including bioinformatics. The course has been developed by the Cambridge Computational Biology Institute and is run by the Department of Applied Mathematics and Theoretical Physics at the Centre for Mathematical Sciences (CMS).

Centre for Scientific Computing MPhil and PhD  - The MPhil programme on Scientific Computing is offered by the University of Cambridge as a full-time course which aims to provide education of the highest quality at Master’s level. A common route for admission into our PhD programme is via the Centre’s MPhil programme in Scientific Computing.

Part III Mathematics  - Part III is a 9 month taught masters course in mathematics.  It is an excellent preparation for mathematical research and it is also a valuable course in mathematics and in its applications for those who want further training before taking posts in industry, teaching, or research establishments. Students admitted from outside Cambridge to Part III study towards the Master of Advanced Study (MASt).  Students continuing from the Cambridge Tripos for a fourth year, study towards the Master of Mathematics (MMath).  The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree. There are over 200 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. 

School of Clinical Medicine Graduate Training Office - Prospective students interested in pursuing a graduate degree course in a subject area related to clinical medicine at the University of Cambridge should consult the School’s individual departmental websites for detailed information about the courses which they run and the University’s Graduate Admissions website for information on the application process and on funding opportunities.

Centre for Doctoral Training in Data, Risk And Environmental Analytical Methods  - The CDT embraces a wide range of world-leading Doctoral research in the area of Big Data and Environmental Risk Mitigation. The CDT research underway seeks to utilise emerging technologies, techniques and tools, to more accurately monitor the environment, enabling cutting edge research. To provide end-users with more integrated information at improved temporal and spatial resolutions to deliver solutions to environmental challenges (both acute and long- term). Funded by  NERC  (the Natural Environment Research Council, NERC Ref: NE/M009009/1), the DREAM (Data, Risk and Environmental Analytical Methods) consortium is made up of Cranfield, Newcastle, Cambridge and Birmingham universities.

Centre for Doctoral Training in Data Intensive Science  - The Cambridge CDT in Data Intensive Science is an innovative, interdisciplinary centre, distributed between the Department of Physics (Cavendish Laboratory), Department of Applied Mathematics and Theoretical Physics (DAMTP), Department of Pure Mathematics and Mathematical Statistics (DPMMS) and the Institute of Astronomy (IoA).

MPhil in Data Intensive Science - This course aims to take science graduates and to prepare them for data intensive research careers by providing advanced training in three key areas – Statistical Analysis, Machine Learning, and Research Computing – and their application to current research frontiers.

Cambridge Digital Humanities - The MPhil provides the opportunity to specialise in a chosen subject area as well as an advanced level introduction to DH approaches, methods and theory. The course provides critical and practical literacy, the chance to advance an extant specialization by re-contextualizing it in relation to advanced theoretical work, and the chance to develop as a DH scholar.

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

• Supports and connects the growing data science and AI research community 
• Builds research capacity in data science and AI to tackle complex issues 
• Drives new research challenges through collaborative research projects 
• Promotes and provides opportunities for knowledge transfer 
• Identifies and provides training courses for students, academics, industry and the third sector 
• Serves as a gateway for external organisations 

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Graduate Applications

The CQIF includes four members of DAMTP Faculty, two affiliated members, and several senior researchers.

We always have to turn away some outstanding applicants: if you are considering applying to us you should also apply widely elsewhere. Applicants who are not UK citizens should also carefully consider the information about funding below, and note the very early deadlines for applications for funding from Foundations and Trusts. Applications to start a PhD in October 2022 will be considered from November 2021 onwards.

Successful applicants are likely to have a first class undergraduate degree in mathematics, physics or computer science, and should ideally also have an M.Sc. or equivalent qualification. Candidates considering applying directly from an undergraduate degree are encouraged to consider applying first to take Cambridge's one-year Masters-level course, the Master of Advanced Study in Mathematics (Part III of the Cambridge Mathematics Tripos). The course includes one or more lecture courses on aspects of quantum information and foundations, as well as courses on a wide variety of other topics in theoretical physics and pure and applied mathematics.

Applications from graduate students to research centres in DAMTP are handled by the Board of Graduate Studies in the first instance, and then administered by the department. Applications for PhD places should thus be made to the Board of Graduate Studies in the first instance, specifying an interest in working at the CQIF in DAMTP. The information needed can all be found on this page . Note that the timetable for applications has some very early application deadlines.

The University's admissions process is quite slow and, beyond the initial acknowledgment of receipt of your application, past experience suggests it could be as late as May before you hear any more from the University. Once the application process has started, your application can be tracked using your self-service account .

Applications for the Part III course should also be made to the Board of Graduate Studies. The information needed can be found on this page .

Our standard method of funding UK and EU graduate students is by grants from the UK Engineering and Physical Sciences Research Council. These are allocated by the department, mostly after the Part III results in mid to late June. EPSRC studentships provide full support for UK students, and cover tuition fees for EU students from outside the UK.

There are some other possible sources for funding (which are not generally restricted to EU students): for example the Gates Foundation, the Cambridge Commonwealth Trust, and a small number of the wealthier Cambridge Colleges. Decisions on these scholarships are made in May. Unfortunately (at least for us!), these funding sources are entirely outside our control or influence; in particular there is nothing we can do to get a decision from them sooner than May. Applications to these organisations and institutions need to be made separately. The University's Board of Graduate Studies web pages --- reached from the above-mentioned links --- have some information; anyone needing clarification or advice should contact either them or the relevant organisation. We have no independent sources of support for non-EU students.

While we try to be helpful where possible, there is normally little that we can add to the information given here. We cannot generally comment in advance on the chances of any individual application to the CQIF being successful or offer advice in putting together an application. Applicants may find it helpful, though, to look at the information on our group web pages, and especially useful to look at some of the recent papers of CQIF members, which can mostly be found on the quantum physics archive . (Some recent papers are also linked from CQIF members' personal pages on this site.)

We normally interview  selected candidates once applications have been reviewed: the timetable for these varies from year to year.

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PhD in Computation, Cognition and Language (MLAL211)

The PhD in Computation, Cognition and Language is a PhD track for students who conduct basic and applied research in the computational study of language, communication, and cognition, in humans and machines. This research is interdisciplinary in nature and draws on methodology and insights from a range of disciplines that are now critical for the further development of language sciences, including (but not limited to) Linguistics, Cognitive Science, Computer Science, Engineering, Psychology and Neuroscience. A variety of PhD topics that fall within this remit are accepted.

Our current primary areas of research are:

• natural language processing
• computational and corpus linguistics
• computational models of human language acquisition and processing
• information extraction, mining, and presentation
• multilingual technology
• educational and assistive technology
• text data technology for health
• computational digital humanities
• computational approaches to the analysis of speech
• digital forensic speech analysis

In British universities, the PhD is traditionally awarded solely on the basis of a thesis, a substantial piece of writing which reports original research into a closely defined area of enquiry. The completion of the PhD thesis is generally expected to take three years, and most funding is based on this assumption. While the PhD is not a taught course, students will benefit from the availability of courses and seminars offered both within the MMLL Faculty and by other departments concerned with language science in Cambridge (e.g. Computer Science and Technology, Education, Engineering, Psychology, MRC Cognition and Brain Sciences Unit). All research students also benefit from a programme of professional training run at various levels within the School of Arts and Humanities, and enabling cross-disciplinary interactions. The programme includes seminars and workshops on e.g., giving conference papers, publishing, applications and interviews, teaching skills, specialist linguistic training. If you wish, you are likely to be given the opportunity of gaining experience in small group teaching for colleges. There may also be opportunities to gain some experience in teaching in the Faculty.

Academic Requirements

Applicants for this course must have a UK First-class Honours Degree or equivalent in linguistics, computational linguistics, artificial intelligence, computer science, or a related discipline.  However, a first-class (distinction level) Masters-level degree is required. The degrees must testify to the applicant's substantial background in linguistics.  Applicants are expected to demonstrate clear evidence of research potential.  Well-developed programming skills are presumed.

Supervision

The Degree Committee for the Faculty appoints a primary supervisor and an advisor for each research student. In some cases, a second, co-supervisor, may be appointed, especially when the research topic is strongly cross-disciplinary. Research students in CCL will have daily contact with the research group within which they are placed. In addition, they should expect a meeting with their supervisor(s) at least once a month. The University of Cambridge publishes an annual Code of Practice which sets out the University’s expectations regarding supervision.

Prospective applicants can get an idea of the range of topics which can be supervised from the following lists of people:

• Staff and their Research Interests
• Full Section Staff List
• Members of the Faculty
• Current PhD Students

Research students are expected to attend weekly research seminars and discussion groups in their research group. They may also attend other relevant research seminars offered by Linguistics or other language science departments in Cambridge. Research students must attend training in research skills. These are offered by Sectional PhD training seminars and the Researcher Development Programme of the University.

There is a normal word limit for the thesis of 80,000 words (including footnotes and appendices but excluding bibliography). The thesis should represent a significant contribution to learning through the discovery of new knowledge or through the connection of previously unrelated facts, or the development of new theory, revision of older views or some combination of these. In writing the thesis you are expected to take account of previously published work on the subject and the thesis should be clearly and accurately written, paying due attention to English style and grammar. Candidates for the PhD in Cambridge are guided by a supervisor, though they will normally also discuss their work with a number of other experts in their field. Following submission of the thesis, an oral (viva) examination is held.

Annual progress interviews constitute a system for the formal monitoring by the Degree Committee of the progress of all students working towards a PhD. Termly progress interviews take place in the fourth year of the PhD.

Postgraduate students are admitted in the first instance for a probationary period during which they are not registered as a candidate for the PhD degree. The first-year interview is the context in which registration as a candidate for the PhD is formally considered. Satisfactory progress is a condition for being registered as a doctoral student and for remaining on the register.

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PhD Programme in Advanced Machine Learning

The Cambridge Machine Learning Group (MLG) runs a PhD programme in Advanced Machine Learning. The supervisors are Jose Miguel Hernandez-Lobato , Carl Rasmussen , Richard E. Turner , Adrian Weller , Hong Ge and David Krueger . Zoubin Ghahramani is currently on academic leave and not accepting new students at this time.

We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its scientific applications. There are no additional restrictions on the topic of the PhD, but for further information on our current research areas, please consult our webpages at http://mlg.eng.cam.ac.uk .

The typical duration of the PhD will be four years.

Applicants must formally apply through the Applicant Portal at the University of Cambridge by the deadline, indicating “PhD in Engineering” as the course (supervisor Hernandez-Lobato, Rasmussen, Turner, Weller, Ge and/or Krueger). Applicants who want to apply for University funding need to reply ‘Yes’ to the question ‘Apply for Cambridge Scholarships’. See http://www.admin.cam.ac.uk/students/gradadmissions/prospec/apply/deadlines.html for details. Note that applications will not be complete until all the required material has been uploaded (including reference letters), and we will not be able to see any applications until that happens.

Gates funding applicants (US or other overseas) need to fill out the dedicated Gates Cambridge Scholarships section later on the form which is sent on to the administrators of Gates funding.

Deadline for PhD Application: noon 5 December, 2023

Applications from outstanding individuals may be considered after this time, but applying later may adversely impact your chances for both admission and funding.

FURTHER INFORMATION ABOUT COMPLETING THE ADMISSIONS FORMS:

The Machine Learning Group is based in the Department of Engineering, not Computer Science.

We will assess your application on three criteria:

1 Academic performance (ensure evidence for strong academic achievement, e.g. position in year, awards, etc.) 2 references (clearly your references will need to be strong; they should also mention evidence of excellence as quotes will be drawn from them) 3 research (detail your research experience, especially that which relates to machine learning)

You will also need to put together a research proposal. We do not offer individual support for this. It is part of the application assessment, i.e. ascertaining whether you can write about a research area in a sensible way and pose interesting questions. It is not a commitment to what you will work on during your PhD. Most often PhD topics crystallise over the first year. The research proposal should be about 2 pages long and can be attached to your application (you can indicate that your proposal is attached in the 1500 character count Research Summary box). This aspect of the application does not carry a huge amount of weight so do not spend a large amount of time on it. Please also attach a recent CV to your application too.

INFORMATION ABOUT THE CAMBRIDGE-TUEBINGEN PROGRAMME:

We also offer a small number of PhDs on the Cambridge-Tuebingen programme. This stream is for specific candidates whose research interests are well-matched to both the machine learning group in Cambridge and the MPI for Intelligent Systems in Tuebingen. For more information about the Cambridge-Tuebingen programme and how to apply see here . IMPORTANT: remember to download your application form before you submit so that you can send a copy to the administrators in Tuebingen directly . Note that the application deadline for the Cambridge-Tuebingen programme is noon, 5th December, 2023, CET.

What background do I need?

An ideal background is a top undergraduate or Masters degree in Mathematics, Physics, Computer Science, or Electrical Engineering. You should be both very strong mathematically and have an intuitive and practical grasp of computation. Successful applicants often have research experience in statistical machine learning. Shortlisted applicants are interviewed.

Do you have funding?

There are a number of funding sources at Cambridge University for PhD students, including for international students. All our students receive partial or full funding for the full three years of the PhD. We do not give preference to “self-funded” students. To be eligible for funding it is important to apply early (see https://www.graduate.study.cam.ac.uk/finance/funding – current deadlines are 10 October for US students, and 1 December for others). Also make sure you tick the box on the application saying you wish to be considered for funding!

If you are applying to the Cambridge-Tuebingen programme, note that this source of funding will not be listed as one of the official funding sources, but if you apply to this programme, please tick the other possible sources of funding if you want to maximise your chances of getting funding from Cambridge.

What is my likelihood of being admitted?

Because we receive so many applications, unfortunately we can’t admit many excellent candidates, even some who have funding. Successful applicants tend to be among the very top students at their institution, have very strong mathematics backgrounds, and references, and have some research experience in statistical machine learning.

Do I have to contact one of the faculty members first or can I apply formally directly?

It is not necessary, but if you have doubts about whether your background is suitable for the programme, or if you have questions about the group, you are welcome to contact one of the faculty members directly. Due to their high email volume you may not receive an immediate response but they will endeavour to get back to you as quickly as possible. It is important to make your official application to Graduate Admissions at Cambridge before the funding deadlines, even if you don’t hear back from us; otherwise we may not be able to consider you.

Do you take Masters students, or part-time PhD students?

We generally don’t admit students for a part-time PhD. We also don’t usually admit students just for a pure-research Masters in machine learning , except for specific programs such as the Churchill and Marshall scholarships. However, please do note that we run a one-year taught Master’s Programme: The MPhil in Machine Learning, and Machine Intelligence . You are welcome to apply directly to this.

What Department / course should I indicate on my application form?

This machine learning group is in the Department of Engineering. The degree you would be applying for is a PhD in Engineering (not Computer Science or Statistics).

How long does a PhD take?

A typical PhD from our group takes 3-4 years. The first year requires students to pass some courses and submit a first-year research report. Students must submit their PhD before the 4th year.

What research topics do you have projects on?

We don’t generally pre-specify projects for students. We prefer to find a research area that suits the student. For a sample of our research, you can check group members’ personal pages or our research publications page.

What are the career prospects for PhD students from your group?

Students and postdocs from the group have moved on to excellent positions both in academia and industry. Have a look at our list of recent alumni on the Machine Learning group webpage . Research expertise in machine learning is in very high demand these days.

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MPhil in Scientific Computing

The MPhil in Scientific Computing provides world-class education on high performance computing and advanced algorithms for numerical simulation at continuum and atomic-scale levels.

Successful candidates will have a 2:1 or first class honours degree (or equivalent) in a science or technology discipline, and an adequate level of computer literacy.

The MPhil is a 12-month full-time master’s degree, which has a taught element and a research element which carry equal examination credit.

Funding sources for postgraduate study are available from the University of Cambridge and external sources such as UK Research Councils and industry.

Graduates of the MPhil in Scientific Computing obtain rigorous research skills and are formidably well-equipped to proceed to doctoral research or directly into employment.

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List of finished PhD students

Below is a list of all the PhD theses so far recommended by the Computer Science Degree Committee to the Board of Graduate Studies for approval (which can in some cases mean that there are still corrections to be made before final approval). Fully approved Cambridge PhDs are listed in the University Library thesis catalog .

All authors are encouraged to publish their approved thesis as a Computer Laboratory Technical Report . Where available, the table below links to that public tech-report version of the thesis. Where available, it also links the local PDF version uploaded by the student , which now also includes files that were in the past collected by Lise Gough in /usr/groups/studentadmin/PhD_theses. (The local PDFs are only accessible to members of the Computer Laboratory and may in some cases not yet contain any final corrections required by the examiners.)

Note: If a Computer Laboratory research student's PhD is not listed here, then it might have been dealt with by the Mathematics Degree Committee (this includes any pre-1987 Computer Laboratory PhD) or by the Engineering Degree Committee (this applies to some early ones in the Digital Technology Group).

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To obtain a PhD degree you must complete three years full-time training (or five years part-time) and carry out an original piece of research which makes a significant contribution to learning in one of the many research areas in the Department. At the same time, the Department expects that students will leave with the wider skills necessary to be successful in either an academic or a non-academic career. Research students are therefore expected to obtain an effective training in research and to broaden their background knowledge, as well as to undertake a novel research project. In their first year, students take a minimum of two taught modules from a wide range of courses offered by the Department. Modules consist of lectures and practical work, and each module involves about 80 hours of work. You will also participate in a researcher development programme during your first year, and you are expected engage in personal development opportunities throughout the PhD in order to develop important transferable skills.

As a research student working in the Department of Engineering, you will work most closely with your Supervisor , who is responsible for guiding your research and training. You can expect at least eight one hour-long individual meetings with your supervisor every calendar year, although it may be much more frequent. You will also have daily contact with the research group you are working within. In addition, you will be assigned an Adviser , who will take an active interest in your progress and be available to provide additional support and advice when needed.

All doctoral research takes place in University of Cambridge facilities. However, the Department and its supervisors have strong links to other institutions both in the UK and around the world. After their first year, students may therefore apply for permission to undertake research in other institutions for extended periods of time. There may also be opportunities to teach small groups of engineering undergraduates to widen your experience and gain valuable expertise in explaining engineering concepts.

At the end of your first year, you will write a 15,000 progress report on your research to date, and discuss your work with two assessors. Passing this assessment is a requirement to continue with the PhD beyond the first year. After completing three years of research, you will submit a 60,000 word thesis on your research and have an oral examination. The final deadline for submission of the thesis is four years after the start date (or seven years for part-time students), but we advise students to aim to submit by either the end of their tenth term, or the end of their funding, whichever is soonest.

The PhD in Engineering can be tailored to suit your particular interests. Applicants must identify a supervisor that they wish to work with on their application form, and contact them directly to discuss their research interests in advance of submitting an application. You can browse current topics of research in the department and identify potential supervisors via the research pages of our website. You should state the name of the supervisor(s) that you wish to work with on your application form, and should also give at least an indication of the topic you wish to undertake research on, so that we can direct your application appropriately.

Further information, including entrance requirements and how to apply, can be found on the online  Course Directory . The Engineering Postgraduate Students website contains resources for current students and may also be of interest to applicants:  www.graduate.eng.cam.ac.uk .

 Academics accepting PhD Students for 2023/24 can be found via the following links;

Electrical Engineering -  https://ee.eng.cam.ac.uk/index.php/graduate-studies/

Mechanics, Materials and Design -  http://www.eng.cam.ac.uk/research/academic-divisions/mechanics-materials-and-design/postgraduate-studies-research-students

Manufacture and Management -  https://www.ifm.eng.cam.ac.uk/education/phd/topics/

Information Engineering:  http://www.eng.cam.ac.uk/research/academic-divisions/information-engineering/postgraduate-studies

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Researchers at MIT recently signed a four-year collaboration agreement with the Novo Nordisk Foundation Quantum Computing Programme (NQCP) at Niels Bohr Institute, University of Copenhagen (UCPH), focused on accelerating quantum computing hardware research.

The agreement means that both universities will set up identical quantum laboratories at their respective campuses in Copenhagen and Cambridge, Massachusetts, facilitating seamless cooperation as well as shared knowledge and student exchange.

“To realize the promise of quantum computing, we must learn how to build systems that are robust, reproducible, and extensible. This unique program enables us to innovate faster by exchanging personnel and ideas, running parallel experiments, and comparing results. Even better, we get to continue working with Professor Morten Kjaergaard, a rising star in the field, and his team in Copenhagen,” says William Oliver, the Henry Ellis Warren (1894) Professor within the MIT Department of Electrical Engineering and Computer Science (EECS), professor of physics, associate director of the Research Laboratory of Electronics, and the head of the Center for Quantum Engineering at MIT.

Oliver’s team will supervise the funded research, which will focus specifically on the development of fault-tolerant quantum computing hardware and quantum algorithms that solve life-science relevant chemical and biological problems. The agreement provides 18 million Danish kroner (approximately $2.55 million) from the Novo Nordisk Foundation Quantum Computing Program to support MIT’s part in the research.

“A forefront objective in quantum computing is the development of state-of-the-art hardware with consistent operation,” says Maria Zuber, MIT’s presidential advisor for science and technology policy, who helped facilitate the relationship between MIT and the Danish university. “The goal of this collaboration is to demonstrate this system behavior, which will be an important step in the path to practical application.”

“Fostering collaborations between MIT and other universities is truly essential as we look to accelerate the pace of discovery and research in fast-growing fields such as quantum computing,” adds Anantha Chandrakasan, chief innovation and strategy officer, dean of engineering, and the Vannevar Bush Professor of EECS. “The support from the Novo Nordisk Foundation Quantum Computing Programme will ensure the world’s leading experts can focus on advancing research and developing solutions that have real-world impact.”

“This is an important recognition of our work at UCPH and NQCP. Professor Oliver’s team at MIT is part of the international top echelon of quantum computing research,” says Morten Kjaergaard, associate professor of quantum information physics and research group leader at the Niels Bohr Institute at UCPH. “This project enables Danish research in quantum computing hardware to learn from the best as we collaborate on developing hardware for next-generation fault-tolerant quantum computing. I have previously had the pleasure of working closely with Professor Oliver, and with this ambitious collaboration as part of our the Novo Nordisk Foundation Quantum Computing Programme, we are able to push our joint research to a new level.”

Peter Krogstrup, CEO of NQCP and professor at Niels Bohr Institute, follows up, “We are excited to work with Will Oliver and his innovative team at MIT. It aligns very well with our strategic focus on identifying a path with potential to enable quantum computing for life sciences. The support aims to strengthen the already strong collaboration between Will and Morten’s team, a collaboration we hope to make an important part of the NQCP pathfinder phase over the coming years.”

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Graduate Programmes Admissions List 2024/25

The Academic Registrar,  Makerere University  has released the admission list to Graduate Programmes (Postgraduate Diplomas,  Masters and Doctoral Degree Programmes) for the  2024/2025  Academic Year. 

The list is here below:

Lumumba Hall renovated to perfection

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On Friday 26 th July 2024, the Contractor- National Enterprise Corporation (NEC) handed over the renovated Lumumba Hall of Residence to the Vice Chancellor, Prof. Barnabas Nawangwe.

Inspecting the renovated Lumumba Hall, the Vice Chancellor disclosed that NEC had performed as per the guidelines and quality standards provided hence fulfilling the expectations of Management, students, alumni, staff and stakeholders in general.

The UGX 9 billion renovation works, which commenced on 27 th June 2023 involved undertaking an overhaul aimed at restoring Lumumba Hall to its original beauty. At the site handover in 2023, the Vice Chancellor stated that Lumumba Hall which was built in the 1960s and officially opened in 1971 was the biggest Hall of Residence, but there had been no major renovation since the time it was constructed.

After 12 months of renovation, the Vice Chancellor was delighted to receive the renovated Lumumba Hall from NEC.   “You can think this Hall has just been built. It has been restored. This points to the wonderful quality works by NEC,” remarked Prof. Nawangwe. He thanked NEC for the quality work and high level of professionalism in the execution of the entire project.

The Vice Chancellor applauded the Government of Uganda for providing all the resources for the renovation of Lumumba Hall as well as Mary Stuart Hall of residence, whose renovation works commenced on Friday 31 st May 2024.

On behalf of the students, the Guild President Vincent Lubega Nsamba acknowledged the Government of Uganda and the Makerere University Management for embarking on the renovation of Halls of Residence within the University.

“The resources have been put to good use leading to a beautiful and magnificent edifice of a new Lumumba Hall. The facility is user friendly for students living with disabilities, which clearly aligns to the broader commitment of inclusivity and diversity,” said Lubega Nsamba.

Commending the quality works, the University Secretary, Mr. Yusuf Kiranda pointed out that the engagement of local companies such as NEC not only contributes to national development, but also showcases the local expertise in the different sectors.

Eng. Brian Buhanda who represented the Managing Director of NEC-Lt. Gen. James Mugira appreciated Makerere University for providing NEC with an opportunity to showcase its potential in the construction sector. He indicated that NEC had gained valuable expertise from this project, which would enrich future ventures.

With the ongoing renovation of Mary Stuart Hall also undertaken by NEC, Lumumba Hall will be occupied by the residents of Mary Stuart Hall. In the University setting, Lumumba Hall and Mary Stuart Hall form the Lumbox solidarity.

Lumumba Hall was named after Patrice Lumumba, a freedom fighter and the first Prime Minister of the Republic of Congo (currently Democratic Republic of Congo). The hall has the capacity to accommodate approximately 752 students.

Prof. Buyinza Mukadasi Appointed Acting DVC Academic Affairs

The Academic Registrar, Professor Buyinza Mukadasi has been appointed Acting Deputy Vice Chancellor (Academic Affairs) of Makerere University , for a period of six (6) months effective 11 th July 2024 to 10 th January 2025 or until a substantive First Deputy Vice Chancellor (Academic Affairs) is appointed whichever comes earlier.

He is a Professor of Forestry Resource Economics and served as the Director, Directorate of Research and Graduate Training (DRGT), Makerere University from 2014 to October 2022. Buyinza holds a PhD in Forest Economics from Gadjah Mada University (UGM), Yogyakarta Indonesia. He holds a number of professional enhancement certificates and Diplomas.

As Director DRGT he was charged with the oversight responsibility of all institutional research grants and graduate training in the university. Prof Buyinza served as the Deputy Director in Charge of Administration and Graduate Training (2010 – 2013); Head, Department of Community Forestry and Extension, Faculty of Forestry and Natural Resources (2003 – 2005, 2008-2010) at Makerere University .  Buyinza grew though the University ranks from a Tutorial Assistant (1993 – 1998) at Gajah Mada University, Indonesia to becoming a Lecturer (1999); Senior Lecturer (2004); Assoc. Professor (2007) and Full Professor (2010) at Makerere University .  He has over 20 years experience of University research and teaching in the field of Forestry and Natural Resource Economics.  He has successfully supervised over 50 MSc. and 10 PhD students in the fields of forestry, environment and natural resources. He has also acted as an external examiner in many regional and international universities. He is a member of many professional bodies and served as the Chairperson, Board of Directors of the National Forestry Authority (2007 – 2013). He was the Institutional Focal person (2010-2022) and Chair of the Board of Management of the Consortium for Advanced Research Training in Africa (CARTA), 2014 – 2018.

Buyinza has published widely in the field of forest resource economics, environmental incomes, economics of biodiversity conservation, and Environmental Incomes for Rural Income and livelihoods. He has authored more than 150 papers in International peer-reviewed referred journals, 4 book Chapters, attended more than 70 conference proceedings and has presented in more than 140 conferences/seminars/workshops.

Buyinza has built a very strong international network of collaborations in research administration and has tremendous capacity for resource mobilization. He has been Principal investigator (PI) of 15 research projects and as Co-Principal Investigator in many other institutional research grants. He is the Coordinator of various externally funded research capacity building initiatives at  Makerere University . He has a wealth of research management experience with special focus on in the field of natural resources economics, and environmental governance.

Advert: Mature Age Entry Scheme – Private Sponsorship 2024/2025

The Academic Registrar, Makerere University invites applications for the Undergraduate Programmes under the Mature Age Entry Scheme only for Private Sponsorship for 2024/2025 Academic Year. Non-Refundable Application fee of Shs. 50,000/= for Ugandans OR $75 Equivalent for Internationals, plus bank charge should be paid in any of the banks used by Uganda Revenye Authority after generating a Payment Reference Number (PRN).

• Apply using the Institution’s Applications Portal URL: https: //apply.mak.ac.ug
• Application is for candidates who passed the Mature Age Entry Examinations of December 17, 2022 and February 24, 2024 only.
• Any candidate who passed the examinations in mentioned above and was not admitted on Government/ Private sponsorship for December 17, 2022 sitting, and for Government sponsorship for February 24, 2024 sitting, is eligible to apply for admission on Private Sponsorship for 2024 /2025 Academic Year.

The closing date for applying will be Friday 26th July, 2024.

Further details can be accessed by following this link.

Prof. Mukadasi Buyinza ACADEMIC REGISTRAR

Admission to Bachelor of Education Degree (EXTERNAL) 2024/25

Mak, Nanjing University of Information Science & Technology Sign Collaboration Agreement

Building Resilience: Makerere Leads Climate Finance Training for Finance Officials

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Physics PhD Thesis Defense: Jeffrey Krupa

Thursday, August 08, 2024 at 3:00pm

Building 24, 24-506 60 VASSAR ST, Cambridge, MA 02139

Dear Colleagues,

You are cordially invited to attend the following thesis defense.

’’Exploring New Frontiers in High Energy Physics: Boosted Resonances Decaying To Quarks, Foundation Models, and Heterogeneous Computing at the CMS Experiment’’ Presented by Jeffrey Krupa Date: Thursday, August 8, 2024 Time: 3 pm Location: Room #24-506  Also available on Zoom at  https://mit.zoom.us/j/92783771430 Committee:   Philip Harris, Michael Williams, Lina Necib Best of luck to Jeffrey!

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Career Guide: Electrical and Computer Engineer Jobs with a PhD

A PhD in Electrical and Computer Engineering is an elite credential.

It opens up a world of advanced technical roles at the forefront of innovation. Upon graduation, ECE doctorates can pursue fulfilling careers as research scientists, respected university professors, senior engineering experts, and executive-level technical leaders. 

With unparalleled knowledge and valuable research abilities, PhD graduates in electrical and computer engineering can elevate their earnings potential while preparing for coveted senior technical and academic positions.

If these opportunities interest you, it’s time to explore the top career paths and opportunities awaiting those with a PhD in electrical and computer engineering.

Overall ECE Salary Potential for PhD Graduates

According to Payscale , electrical and computer engineering PhDs have an average salary of $149,000 in 2021.

While the PhD journey requires substantial effort, this elite credential pays in the long run. ECE PhDs can expect premium salaries along with accelerated advancement into leadership roles thanks to their elevated expertise.

Electrical and Computer Engineering Jobs for PhD Grads

Research Scientist

As research scientists, ECE doctorates pearhead cutting-edge studies and development projects to solve complex technical challenges. Their primary responsibilities involve:

• Identifying problems or knowledge gaps
• Formulating hypotheses
• Designing and executing experiments
• Analyzing data
• Developing or enhancing technologies based on their findings.

Professionals with a PhD in electrical engineering earn an average salary of $137,525 per year as research scientists according to PayScale.  

Employers eagerly seek the extensive research training and specialized technical prowess that ECE PhDs gain through years of intensive study culminating in their doctoral dissertations. Their proven hands-on experience planning and executing original research from conception to publication gives them a distinct edge for research scientist roles.

Where you can work

• Major technology leaders like Microsoft, IBM, Intel, Apple, and Qualcomm
• Government agencies like NASA and the Department of Defense
• Top research universities and national laboratories
• Medical and biotech firms

Earning a PhD is a requirement for securing a tenure-track faculty position. As professors in university ECE departments, PhDs can:

• Teach courses
• Develop curricula
• Advise students
• Conduct research
• Publish scholarly papers
• Secure research grants
• Serve in administrative roles. 

Most especially, electrical and computer engineering professors impart advanced technical knowledge across areas like electronics, telecommunications, computer architecture, embedded systems, VLSI, photonics, and more — while earning an average of $144,115 per year, according to Salary.com .

Many top-ranked engineering programs actively recruit PhDs for ECE professor roles. Smaller colleges and universities also hire these doctorates to teach and conduct research.

Senior Hardware/Software Innovator

Senior hardware and software engineers are elite technical experts who lead complex, pioneering projects. With a PhD in ECE, engineers may head teams developing next-generation computer hardware including:

• Quantum hardware
• Biometric hardware
• Wearable ecosystems
• Sustainable technologies
• Embedded IoT devices
• Groundbreaking software for AI, machine learning, robotics, cybersecurity and more.

Salary.com data shows senior hardware engineers with PhDs earn $114,930 per year on average, while their senior software counterparts with doctorates average $120,906 to $126,967 annually .

The rigorous, hands-on doctoral research required provides hardware and software engineers with the specialized knowledge and advanced problem-solving abilities to succeed in senior technical roles. Their proven capacity to tackle complex challenges through novel research makes PhD holders very attractive hires.

Innovative technology leaders like Apple, Google, Nvidia, Qualcomm, AMD, and others aggressively recruit PhDs for elite senior engineering roles to accelerate the development of products and services.

Engineering Leader

At the director and VP levels, engineering leaders must have skills (and the credentials to prove it), so they can carry out their important work:

• Managing large technical teams
• Spearheading strategic initiatives. 
• Providing vital technical vision, guidance and mentorship in areas like computer architecture, hardware design, networking, embedded systems, and beyond.

According to Glassdoor, a Vice President of Electrical Engineering earns an average base salary of $140,000 to $241,000 per year.

Through expertise gained in their doctoral research, ECE PhDs position them well for executive engineering leadership at major corporations including:

• Lockheed Martin

Taking Advantage of Career Opportunities in ECE: Keys to Success

When launching their careers, ECE PhDs should look beyond the obvious company types and roles. Their rare combination of deep technical knowledge, research abilities, analytical skills, and problem-solving expertise has remarkable value across diverse industries.

• Networking: Building connections through your academic network can prove invaluable. Alumni associations, advisors, and professors can facilitate introductions to companies of interest
• Attending conferences: Events related to your specialization fosters great connections too.
• Nailing interviews:  Highlighting tangible achievements like published papers, patents, products, implemented solutions, and other concrete examples showcases your capabilities you bring employers.

A rewarding career is possible with the right education: SMU Moody's PhD in ECE program has you covered

Earning your PhD in computer engineering and electrical engineering is a “high-reward” degree. 

With the right information, a well-chosen program, and strong advocates by their side, ECE doctorates are perfectly positioned for professional success across academia, government, and virtually every industry in need of elite engineering expertise.

Looking for those things doesn’t have to be a hassle — download our resource, A Complete Guide to Earning Your Ph.D. in Electrical and Computer Engineering , and take the next step towards earning the degree that’s propelling society forward.

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New Computer Science Education Program helps teachers reach goals of rigid state criteria

By ALEXANDRA SACCONE

Graduate student, Department of Environment and Sustainability

Published July 24, 2024

The Graduate School of Education is offering a new computer science fluency and preparation program for K-12 teachers this fall that aims to help them meet New York’s Computer Science and Digital Fluency Standards , a series of rigid criteria for K-12 curricula developed by the Board of Regents in 2020. 

The Computer Science Teacher Preparation Program, one of the first in the state, was first offered to a pilot group in summer of 2023. Considered a resounding success, program director Chris Proctor gave the go-ahead to open registration for fall 2024. The timing is no coincidence: Beginning Sept. 1, all computer science teachers in New York State must be certified, ensuring all K-12 students receive the same standard of computer science education.

“Recognizing the upcoming need for high-quality computer science teachers committed to educational excellence and equity, UB’s Graduate School of Education decided to create a computer science teacher preparation program,” explains Proctor, assistant professor of learning and instruction. 

The program has varying tracks, depending on students’ needs. For working computer science (CS) teachers, the additional certification track is a flexible sequence of five remote courses designed to fit teachers’ schedules. “The goal of this track,” Proctor says, “is for teachers to learn CS and how to teach CS at the same time, drawing on their prior experience as teachers.”

The signature track — the initial/professional certificate track — is designed for preservice teachers looking to receive a CS certification along with their master’s degree in education.  

“It’s the best possible preparation for a career as a CS teacher and it’s a great deal. This is a two-year program — after a year of coursework, students have a yearlong apprenticeship in a CS classroom. You come out with initial and professional certification, along with a master’s,” Proctor says. 

Preservice teachers currently earning certification in another area can add a CS certification through the program, even if they have no prior background in CS. 

This course is just the beginning of creating a better future for the next generation, Proctor says. He hopes to see Western New York regain its historic role as a leader in innovation and social change, with CS and technological literacy at the forefront. He cites social movements, such as abolitionism and women’s rights, as examples of Western New York’s long-standing position as a leader of world-changing movements.

“I want our youth to see a bright future in Western New York — both for economic prosperity and the chance to work toward issues such as social justice and climate resilience,” he says. “CS is a key part of this vision. We need every child to have the opportunity to study CS, and through CS we need to transform our education systems so they work better for every child.”

Applications for fall 2024 are now open now, and Proctor  is available to meet with current and future CS teachers interested in the program. 

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