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Department of Computer Science and Technology

A programme here promoting the use of machine learning to tackle major scientific challenges is offering funding for PhD students starting next autumn.    

The Accelerate Programme for Scientific Discovery is a major initiative here. It is building a community of researchers working at the interface of machine learning and different scientific domains with the aim of accelerating the pace of scientific discovery. As part of this, it is now offering PhD studentships. These will support three years of study, covering course fees (at either international or national rates) and a stipend.

Candidates applying here to study for a PhD in Computer Science starting in autumn 2022 can apply for these studentships. The successful candidates will develop a project at the intersection of machine learning and a scientific discipline, pursuing research that contributes both to the advancement of that discipline and to progress in machine learning.

Current areas of interest for the Programme include the use of machine learning to advance research relating to:

  • Applied mathematics and theoretical physics: how can we use machine learning to better understand complex geometries and create new understandings of space-time or quantum gravity?
  • Genomics and computational biology: how can machine learning-enabled advances in genomics help us better understand the building blocks of living systems and how they contribute to individual health and wellbeing?
  • Psychiatry: how can researchers and clinicians use machine learning tools to better understand and predict mental health conditions?

Research topics
Applicants are invited to propose topics that would advance research in one of these themes, or that bridge these areas of research.

In developing project ideas, applicants may wish to seek inspiration from the work of research leaders connected to the Programme:

Bianca Dumitrascu (pictured top right), Accelerate Science Research Fellow, Department of Computer Science and Technology
Challenger Mishra (pictured right), Accelerate Science Research Fellow, Department of Computer Science and Technology
Sarah Morgan (pictured below right), Accelerate Science Research Fellow, Department of Computer Science and Technology
Carl-Henrik Ek, Senior Lecturer in Machine Learning, Department of Computer Science and Technology

Key skills and interests
The successful candidates will have:

  • a strong interest in working at the interface of machine learning and the sciences;
  • excellent oral and written communication skills;
  • good team-working skills, ideally with experience of working in interdisciplinary teams; and
  • strong motivation for their proposed project.

Eligibility
Applicants will be expected to:

  • have a 1st or strong 2.1 degree in a related subject;
  • hold (or be studying for) a master’s degree in a relevant specialist area; and
  • have applied for the PhD in Computer Science here (for adnission in autumn 2022)
     

Interested candidates are encouraged to make informal contact with potential supervisors before making an application.

Applying
To apply for the Accelerate studentships, candidates should complete this application form.

The form seeks information about your skills, experiences, and motivations for joining the Accelerate team. It also requires you to submit your research proposal, CV, and references. Applications close at midnight on 3 December 2021.

To be considered for the studentship, you must also have applied for the PhD in Computer Science at Cambridge University. This is a separate application process. Please see the University Graduate Admissions website for details of the University admissions process.

Applications to the PhD programme and applications for the Accelerate Studentships will be considered separately. However, you should submit  the same research proposal, CV and reference documents for both.

For advice about potential supervisors and the application process, including advice on which department to apply to, please contact the programme coordinator by emailing accelerate-science@cst.cam.ac.uk

FAQs

What does the Accelerate studentship offer?
The Accelerate Programme values multi-disciplinary approaches to modern scientific challenges. As such, the studentships will afford the opportunity to establish new cross-disciplinary collaborations involving researchers in other departments and institutions. To facilitate this, the PhD candidates will have the opportunity to audit courses offered in associated departments, and will have the option to be mentored by a researcher in another department. The candidates may be provided with a desk space in an associated department subject to availability of space and funds.

Funding from Accelerate is available to support three years of study, covering course fees (at either international or national rates) and a stipend. To see current funding rates, please use the University’s calculator.

What information do I need to submit in my application?
The Accelerate Studentship Application Form asks for your contact details, your motivations for joining the Accelerate Programme, and your research proposal and CV. (These should be the same documents as you have submitted in your application for the PhD in Computer Science.)

When do interviews for the Accelerate studentships take place?
Interviews and candidate selection will take place in early January.

What happens next?
We will review applications in December, and invite shortlisted candidates to interview in January. In parallel, your application will also be considered for the PhD Computer Science. For further information about the process, please visit the Computer Science PhD degree pages. For further information about the process of applying for a PhD at Cambridge, please visit the University of Cambridge PhD in Computer Science web page.

How do I apply for a PhD in Computer Science?
You should apply for the PhD in Computer Science through the University of Cambridge Applicant Portal. Once you have selected your course in the University of Cambridge Postgraduate Course Directory, click the 'Apply Online' button to be directed to the Applicant Portal.

In that application form, you will have the option to apply to various other funding sources. We encourage candidates to apply for all funding sources for which they are eligible.

Where can I find further advice?
If you have questions about the Accelerate PhD studentship, please contact the programme coordinator at accelerate-science@cst.cam.ac.uk 

 

Research group: 

Published by Rachel Gardner on Monday 25th October 2021