Research Assistant/Associate in Efficient Machine Learning Systems for Earth Observation (Fixed Term)

Department/Location: Department of Computer Science and Technology, Cambridge 

Applications are invited for a Research Assistant or Research Associate to work on efficient machine-learning systems for earth observation. The post holder will be part of the Computer Architecture group under the guidance of Prof. Robert Mullins.

The role involves developing new low-power systems and algorithms to significantly enhance the capabilities of onboard AI when used within small satellites. The project is a collaborative effort involving teams at the University of Manchester and University of Southampton and partners at the Alan Turing Institute and HMGCC. The research will seek innovations at both the software and hardware level. The use of a novel memory system and recent advances in low-power machine-learning accelerators will create significant scope to explore new research directions. On-board processing tasks will include object detection, compression, interpretation and various image retrieval tasks. The "Perfect Recollection for Clearer Insight" project is funded by EPSRC.

Successful candidates at the Research Associates must hold a PhD in a relevant subject, at the Research Assistant level must hold a Masters in a relevant subject area or equivalent. Excellent knowledge of machine learning and experience of applying machine learning techniques is expected. Familiarity with efficient ML techniques, edge AI hardware platforms, efficient and low-power computing techniques, ML for earth observation would be desirable.

Applicants should be prepared to collaborate with other project researchers to help develop complete hardware and software demonstrators. They will have excellent programming skills (e.g. in Python, C++, etc.).

Pre-employment screening

The successful candidate will be required to undergo security checks, to be carried out by the National Security Technology Innovation Exchange (NSTIx) before the appointment is confirmed.

Fixed-term: The funds for this post are available until 31 May 2026 in the first instance.

To apply online for this vacancy and to view further information about the role, please click on the apply button above.

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

Informal enquiries can be made by contacting Robert Mullins at Robert.Mullins@cst.cam.ac.uk

If you have any queries about the application process please contact personnel-admin@cst.cam.ac.uk.

Please quote reference NR41691 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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