University of Cambridge

Job Opportunities


Research Assistant/Associate in Machine Learning (Fixed Term)

We are seeking three postdoctoral researchers to join an exciting and significant research programme Machine Learning for Tomorrow which is jointly run by the Cambridge Machine Learning Group at the University of Cambridge ( and Microsoft Research Cambridge (

The goal of the programme is to develop new fundamental machine learning tools that will enable AI systems to be deployed in an efficient, flexible, robust and automated way. These new tools will be tested on a range of tasks drawn from healthcare, productivity tools, and gaming.

The postholders will be supervised by Dr Richard E. Turner and Dr José Miguel Hernández Lobato from the Machine Learning Group in the Department of Engineering. The projects will be co-supervised by Dr Andrew Fitzgibbon, Dr Katja Hofmann, Dr Aditya Nori, and Dr Sebastian Nowozin at Microsoft Cambridge.

The programme is funded by Microsoft Research and an EPSRC Prosperity Partnership grant.

Key responsibilities include working on deep learning, probabilistic modelling, computer vision, Bayesian methods, Bayesian optimisation, deep learning for structured data (including graph neural networks), meta-learning, automated machine learning, continual learning, few-shot learning.

Successful applicants will have or be near to completing a PhD in Computer Science, Information Engineering, Statistics or a related area, with extensive research experience and a strong publication record. Excellent mathematical and programming skills are essential. Experience in one or more of machine learning, statistics, or computer vision is highly desirable. 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.

Salary Ranges: Research Assistant: £26,715 - £30,942; Research Associate: £32,816 - £40,322

Fixed-term: The funds for this post are available for 36 months in the first instance.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload your Curriculum Vitae (CV), a covering letter, and 2 relevant publications in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

If you have any questions about this vacancy or the application process, please contact: Mrs Catherine Munn by email:

Please quote reference NM24012 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.

Further information

Apply online