Research Associate in Machine Learning

About the Role

Applicants are invited for the post of a Research Associate in probabilistic machine learning applied to cancer research. You will join a team of probabilistic modelling and machine learning researchers developing new principles and models for AI-assistants in cancer, which are able to help domain experts even when the goals are only partially known, such as in the beginning of scientific research. This will require expertise on multiple topics; you are expected to have experience in one or more of these and be interested in working with experts on the others.

Initial applications will include decision making in personalized medicine, steering experimental design in cancer clinical trials, and design of digital twins for decision making in oncology. Prior experience in working in the biomedical domain is a plus.

The Team

The team is part of a new initiative between the Centre for AI Fundamentals being established at the University of Manchester and the Manchester Cancer Research Centre (MCRC). You will have excellent opportunities for working with top-notch collaborators on both machine learning and oncology research, targeting to deliver benefits to patients.

The MCRC is a unique partnership founded in 2006 by The University of Manchester, Cancer Research UK and The Christie NHS Foundation Trust. Since its creation, the MCRC partnership has expanded to encompass cancer research activities across Manchester, driving a consistent, compatible and integrated cancer research strategy with the ultimate aim of creating a future free from the burden of cancer.

Requirements

• Experience in one or more of the following: advanced user modelling, automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning and inverse reinforcement learning, and simulator-based inference.
• Interest in working with experts on areas where you lack primary experience.
• Prior experience in the biomedical domain is a plus.
• Applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI).