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Research Associate in Causal AI

The University of Edinburgh - Institute for Imaging, Data and Communications - School of Engineering

Location: Edinburgh
Salary: £39,347 to £46,974 (Grade 7)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 9th May 2024
Closes: 17th June 2024
Job Ref: 10473

Contract type - Fixed term - 3 years

Full time - 35 hours per week

Posts x 4

The opportunity:

The School of Engineering seeks to appoint four Research Associates in Causal AI. These Research Associate positions will contribute to the EPSRC funded CHAI AI Hub and the VIOS group at the University of Edinburgh.

We are looking for enthusiastic postdoctoral researchers to join our team led by Prof. Sotirios Tsaftaris (vios.science) in the prestigious high-profile CHAI AI Hub [www.chai.ac.uk] funded by EPSRC to help us develop new causal AI methods as applied to a variety of healthcare applications co-created within an ecosystem of partners and stakeholders. Our aspiration is to change the future of healthcare precisely because we devise better AI methods rooted in causal.

Areas of particular interest include generative models, representation learning, causal predictive models.

The candidate will:

  • Join a dynamic, international team of several postdocs and students working in AI at the University of Edinburgh –a powerhouse in artificial intelligence, engineering and medicine; 
  • Contribute to a national center of excellence where deep learning and AI meets real healthcare data directly addressing industry and societal needs; and
  • Visit and interact with academic partners at Imperial College London, Kings College London, University College London, The University of Manchester and The University of Exeter as well as large body of industry, policy and government stakeholders (more than 50)
  • Interact with more than 80 affiliated researchers and 8 PDRAs and 11 PhD students of CHAI.

This post is full-time (35 hours per week), however, we are open to considering flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working weekly arrangement subject to planning.

Your skills and attributes for success:

  • A relevant PhD
  • Expertise in the areas of interest above evidenced by related publications in well-regarded venues
  • An ability to deliver quick proof-of-concepts of your original thinking
  • Good communication skills and ability to work within a team
  • A positive attitude illustrating enthusiasm in high risk/reward open-ended research
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