Dear All, We are looking for a Post-Doctoral research fellow to join our machine learning effort to establish the computational foundations for an “AI clinician” (Komorowksi et Faisal, 2018, Nature Medicine; Li et Faisal, 2020, ICLR AI4Health). While a “fully autonomous doctor” is far more ambitious (and perhaps undesirable) than self-driving cars (Topol, 2019, Nature Medicine), our goal is to link our work in the established foundations of clinical decision recommendation systems and evaluate our developments in a meaningful clinical setting. This vision in turn requires the development of novel RL techniques, which are at the heart of this fellowship, such as causal inference in RL and explainable RL (XRL). We have previously shown that RL and Bayesian Optimization can be applied for learning optimal interventions in closed loop (Bohte et al, 2013, Lorenz et al, 2016). We work on methods allowing us to train RL agents interactively (off-policy policy estimation) on historical data of medical interventions (“actions”) and patient responses to them (“state”). We want to build on our groundwork drawing on causal inference, deep- and kernel-based machine learning (Liu et al, 2018, NeurIPS; Parbhoo et al, 2018, PLOS1; Peng et al, 2018, AMIA) and explainable RL (Shafti et al, IROS, 2019) for the emerging domain of RL for medical interventions. Crucially, we believe that Machine Learning for medical intervention may have a larger impact on health than diagnostics, as treatment is where medicine really starts helping people. Crucially, we are working on both the theory and application for RL in healthcare and have as a team already the necessary regulatory approvals for clinical evaluations in our university hospitals are in place and already recruited clinical staff and hospital IT teams. Moreover, as our domain application is the optimal treatment of patient intensive care units, the PostDoc will have the opportunity to join the fight against Covid-19 to save lives by better understanding. Our lab is leading the data science effort for the UK national service evaluation in critical care (https://www.imperial.ac.uk/artificial-intelligence/research/covid/covid-icu/) and is thus working on data from ICUs across an entire country to identify optimal treatment policies. Advert here: https://www.imperial.ac.uk/jobs/description/ENG01259/research-associate https://www.jobs.ac.uk/job/BZP190/research-associate Applications can be received after the advertised deadline (which will be also extended due to Covid-19). Please do reach out to me to find out more. kind regards Aldo -- Aldo Faisal Director, Centre in AI for Healthcare – https://ai4health.io Reader in Neurotechnology -- https://FaisalLab.org Data Science Institute, Dept. of Computing & Dept. of Bioengineering Imperial College London