Research Associate in Machine Learning (2 positions available)

Applicants are invited for the post of a Research Associate in probabilistic machine learning.

You will join a team of probabilistic modelling and machine learning researchers developing new principles for AI-assistants, which are able to help their users 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 of the others. Keywords include 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. Initial applications will include decision making in personalized medicine, steering experimental design in drug design and synthetic biology, and design of digital twins and decision making with them. Prior experience on the application domains is a plus but not required.

The team is funded by an UKRI AI World-Learning Researcher Fellowship, and will be based in a new Centre for AI Fundamentals being established at the University of Manchester. You will have excellent opportunities for working with top-notch collaborators on use cases in application fields in the University of Manchester and industry, and machine learning collaborators at The Turing Institute and ELLIS, in the new ELLIS Unit Manchester .

The Department is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The Department holds a Bronze Award for their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff to achieve a god work-life balance. We positively welcome applications from women for this post. All appointments will always be made

on merit. For further information, please visit: (insert website hyperlink) http://www.manchester.ac.uk/connect/jobs/equality-diversity/awards/athena-swan/

Our University is positive about flexible working – you can find out more here

Blended working arrangements may be considered

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting, and interviews:

Name: Samuel Kaski

Email: [email protected]

General enquiries:

Email: [email protected]

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Further particulars including job description and person specification are available on the University of Manchester website - click on the 'Apply' button above to find out more