Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference

The International Society for Bayesian Analysis; Manchester; On-site; GBP 100,000 - 125,000; Full time

Job summary

A leading research institution in Manchester seeks Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference. The role involves fundamental research and exploring applications in medicine, synthetic biology, and AI. Ideal candidates will have a PhD in a relevant field and experience with Bayesian methods. This is an exciting opportunity to work with top collaborators and contribute to innovative research initiatives.

Qualifications

• PhD in a relevant field (e.g., Machine Learning, Statistics).
• Experience in probabilistic modelling and Bayesian methods.
• Interest in experimental design and decision-making.

Responsibilities

• Conduct fundamental research in probabilistic modelling.
• Explore methods to steer machine learning systems.
• Collaborate with international partners on various projects.

Skills

Advanced user modelling

Bayesian inference

Machine teaching

Reinforcement learning

Job description

Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference

Aug 11, 2021

Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference

I am looking for researchers to my new team in Manchester, UK, funded by the UKRI Turing AI World-Leading Researcher Fellowship programme “Human-AI Research Teams – Steering AI in Experimental Design and Decision-Making”. Closing date of call: September 6, 2021.

The research is fundamental research in probabilistic modelling and Bayesian inference, applied to the exciting problems of how do we steer machine learning systems. Particularly challenging is to steer when we cannot (yet) precisely specify our goal, and ultimately we would like to have machine learning systems that help us in experimental design and decisions.

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 with or without multiple agents, and simulator-based inference. I am not expecting anyone to master all of these, though if you do, please apply immediately…

The team will have excellent opportunities of applying the methods to medicine, especially cancer research and remote medicine; experimental design in synthetic biology and drug design; and digital twins. We have top-notch collaborators in each, both in Academia and in companies, locally and internationally. We can also discuss jointly funded positions with partner companies, hospitals or collaborator groups.

More info about these positions and a link to the application portal:

1. Because we are there
2. Great university, with fluent collaboration with outstanding groups of application fields
3. It is the place to be right now for machine learning. New Fundamental AI Research Centre with several new academics is being launched, on top of the already wide AI activity including Turing Institute partnership with 27 Turing Fellows and ELLIS Fellows.
4. The most livable city in the UK (https://www.investinmanchester.com/why-manchester/living-in-manchester/quality-of-life )