Applicants are invited for the posts of Research Associate or Research Fellow in Machine Learning to work with AI Researchers in the Centre for AI Fundamentals at the University of Manchester.
You will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental ML work, and allows attacking new applications which make a difference, for instance in scientific research. Different team members have different expertise, and by working together are able to address more novel problems. Keywords include: automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulator-based inference.
The post-holder will work on a project from Professor Kaski’s UKRI Turing AI World-Leading Fellowship. Research here includes work to develop new principles and methods for Advanced User Modelling, sequential decision making and Automatic Experimental Design, with and without a Human-in-the-Loop.
A PhD (or equivalent) in a relevant discipline is required. You should have excellent organisational skills and the ability to work well both in a team and using your own initiative. Experience in research methods and techniques to work within established research programmes is essential.
What you will get in return:
- Fantastic market leading Pension scheme
- Excellent employee health and wellbeing services including an Employee Assistance Programme
- Exceptional starting annual leave entitlement, plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at a range of major retailers
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
Our University is positive about flexible working you can find out morehere
Hybrid working arrangements may be considered.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Any CV’s submitted by a recruitment agency will be considered a gift.
Enquiries about the vacancy, shortlisting and interviews:
Name: Isabel Machado
Email:
General enquiries:
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Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
