Research Assistant in Machine Learning (Fixed Term)

Two positions exist for a Research Assistant in the Department of Engineering to work on collaborative projects between the groups of Hong Ge at the Computational and Biological Learning Lab, Department of Engineering, University of Cambridge (https://mlg.eng.cam.ac.uk/), the Alan Turing Institute, the MRC Biostatistics Unit at the University of Cambridge (https://www.mrc-bsu.cam.ac.uk/), and the Stan community.

The post holder will be located in Central Cambridge, Cambridgeshire, UK.

The project aims to synthesise and advance the lessons learned from the continued development, use, and maturation of modern Bayesian modelling frameworks such as Stan, Turing.jl, PyMC, their associated automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special consideration will be paid to computationally intensive modelling components such as ordinary and stochastic differential equations and (approximations to) non-parametric modelling components such as Gaussian Processes. The project will be based on the following key publications:

• TE Fjelde, K Xu, D Widmann, M Tarek, C Pfiffer, M Trapp, SD Axen, X Sun, M Hauru, P Yong, W Tebbutt, Z Ghahramani, H Ge (2025) Turing.jl: a general-purpose probabilistic programming language. ACM Transactions on Probabilistic Machine Learning, https://dl.acm.org/doi/pdf/10.1145/3711897
• A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020) Bayesian Workflow, https://arxiv.org/abs/2011.01808
• B Carpenter, A Gelman, MD Hoffman, D Lee, B Goodrich, M Betancourt, M Brubaker, J Guo, P Li, A Riddell (2017). Stan: A probabilistic programming language. JOSS, https://www.jstatsoft.org/article/view/v076i01

The key responsibilities and duties are:

• Undertaking basic research, formulating research questions and pursuing them using mathematical modelling and numerical simulations.
• Assisting with teaching-related activities.
• Liaising with colleagues and students on routine matters and developing new collaborations.
• Planning own day-to-day research activity.

The candidate should have (or be close to obtaining) an undergraduate/master's (or equivalent experience) in mathematics, computer science, machine learning, information engineering or a related field.

Interviews will be conducted via Zoom.

Salary Ranges: *Research Assistant: £33,002 - £35,608

Fixed-term: The funds for this post are available until 30 September 2026 in the first instance.

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

Please ensure that you upload your Curriculum Vitae (CV) including a publication list and a covering letter 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 Prof Hong Ge may be contacted, for queries of a technical nature related to the role or the application process, please contact: the CBL group administrator Kimberly Cole by sending an email to kc429@cam.ac.uk.

Please quote reference NM46961 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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