Applicants are invited for the post of Research Fellow in probabilistic machine learning.
You will join a team of probabilistic modellers 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 on 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 Fundamental AI Research 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.
Manchester has a long and distinguished track record in the research and teaching of core Computer Science, and across interfaces to adjacent disciplines. Founded upon the pioneering work of Williams, Kilburn and Turing, the School was the first academic Department of Computer Science in the UK and one of the first to run an undergraduate programme. The research strength of the school is reflected in consistently strong returns in UK research assessment exercises (5* in RAE 2000, 2nd in Research Power in RAE 2008, 4th in overall GPA in REF 2014 and ranked equal 1st for research environment).
The School is committed to promoting equality and diversity, including the Athena SWAN charter for promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. The School holds a Bronze Award for their commitment to the representation of women in the workplace and we particularly welcome applications from women for this post. All appointments will be made on merit. For further information, please visit:
https://www.manchester.ac.uk/connect/jobs/equality-diversity-inclusion/awards/athena-swan/
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 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: Professor Samuel Kaski
Email: samuel.kaski@manchester.ac.uk
General enquiries:
Email: People.recruitment@manchester.ac.uk
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.
