Imperial College London (ICL)

Research Associate in Reinforcement Learning for Healthcare

Imperial College London (ICL)

London, United Kingdom

Department of Computing

Research Associate in Reinforcement Learning for Healthcare

South Kensington Campuses

Research Associate salary £41,593 – £49,210 per annum*

Full-time, Fixed term to start ASAP for 2 years with the possibility for extension

Job Summary

Our vision is to establish the computational foundations for an “AI clinician”, an AI system informed by millions of patient records that is using Reinforcement Learning (RL) to learn optimal treatment policies for critically ill patients (Komorowksi et Faisal, 2018, Nature Medicine; Gottesman et al, 2019, Nature Medicine). Prof Aldo Faisal, has been awarded a prestigious UKRI Turing AI Fellowship in Reinforcement Learning for Healthcare.

Our machine learning research goal is centred on developing what is needed as a theoretical foundation for taking our “AI clinician” proof-of-principle all the way to clinical deployment,and expanding its capabilities and responsibilities. Our Research Associates doing fundamental work will be supported by a team of experienced Researchers and a program grant to take the AI Clinician through the regulatory and technical challenges of clinical deployment. The AI Clinician programme is grounded in the established foundations of clinical decision support systems, which will run as a bed-side recommender system watching over the patients state second-by-second and prompting specific clinical interventions to undertake as the patient state evolves.

We are uniquely placed to take our machine learning developments into a meaningful clinical setting, as we have been awarded with generous funding by the UK’s Ministry of Health/NHS-X to setup a globally unique AI for Healthcare testbed for reinforcement learning interventions in 4 intensive care units across Central London. On the clinical side of the AI Clinician we are collaborating with world-leading intensive care clinicians (Anthony Gordon & Matthieu Komorowksi) also at Imperial College. Our project has the support of regulatory experts and specialised medical device units that support us in taking our entire research program all the way to clinical deployment in a live hospital environment.

The overall research environment is corresponding to our ambition, the Departments where Aldo Faisal’s research group is based has been consistently ranked top 3 in the UK, and Imperial College has been consistently ranked in the top-10 universities world-wide. Imperial College boasts a world-leading ecosystem of AI for Healthcare research across the breadth of both AI and Medicine, and hosts among other things the pioneering UKRI Centre in AI for Healthcare (directed by Aldo Faisal), as well as the AI network, comprising over 200 faculty and 1000 Research Associates and PhD Students at Imperial that work in AI.

Duties and responsibilities

The aim of the project is the advancement of foundational Reinforcement Learning methods with the immediate application to clinical intervention and involves the unique opportunity to develop core machine learning theory and see it evaluated with clinical end-users as needed.

We are therefore searching for our UKRI Turing AI research programme areas at the interface of:

  1. Causal Inference & Reinforcement Learning

(see Barenboim & Pearl, 2016; Johnson et al 2017; Gottesmann et Faisal…, 2019, Nature Medicine).

  1. Foundations of Reinforcement Learning

(including Distributional RL & Fusing Off-policy & On-Policy learning; Off-Policy Learning in POMDPs; Neural ODEs for RL, e.g. see Li & Faisal, 2021, AAAI)

  1. Probabilistic (Data-Efficient) learning for Time Series and System Identification

(GPs, GPLVMs, GPAR, VAEs, e.g. see Xiloyannies et Faisal, 2017).

Our vision requires the development of novel machine learning techniques and are thus looking for bright researchers that are keen to develop meaningful machine learning, that they can see come through to real-world application during their work.

Essential requirements

  • a PhD (or near to completion) or equivalent in a relevant field*
  • Relevant computer science/engineering/mathematics/physics or exceptional bio-science undergraduate background
  • Experience in the field of (one more multiple) Reinforcement Learning, Machine Learning, Robotics, Computational Neuroscience, Recommender Systems Neural/Behaviour Data Analysis, Time Series Analysis, or relevant related backgrounds in control systems or Mathematics
  • Strong analytical mathematical skills
  • Strong programming skills
  • Strong machine learning skills.

Please see job description for full list of essential requirements. 

*Candidates close to completion of their PhD will also be considered but will be initially appointed as a Research Assistant within the salary range £36,694 – £39,888 per annum.

How to apply

For further details on this opportunity visit and search using vacancy reference number ENG02137. In addition to completing the online application, candidates should attach:

  • A full CV
  • A short statement indicating what you see are interesting issues relating to the above post and why your expertise is relevant

Informal enquiries regarding post please contact Aldo Faisal:

For queries regarding the application process contact Jamie Perrins:

Closing Date: 29/05/2022 (midnight)

Please apply via recruiter’s website.