Post-Doctoral Research Associate in Machine Learning/Machine Learning Scientist

We invite applications for the position of Postdoctoral Research Associate in Machine Learning/Machine Learning Scientist to join the Deep Medicine programme at the Nuffield Department of Women’s and Reproductive Health (NDWRH), University of Oxford.

The successful candidate will join a multi-disciplinary group of machine learning scientists, epidemiologists and clinicians at Deep Medicine who lead pioneering research in precision medicine with a focus on cardiovascular health.  

The researcher will be expected to lead, build upon and advance this work in order to integrate various HER data sources and other omics database and build multi-type and multi-model AI solutions for risk prediction. Working with some of the largest and most comprehensive EHR, in the world, such as CPRD and UK Biobank as well as more niche “Omics” datasets, the project provides a unique opportunity to apply advanced techniques from machine learning and conduct high-impact research, while contributing to the broader goals of Deep Medicine. 

The objective of the project is to develop and enhance a range of Transformer-based models to predict the risk of key clinical outcomes, such as all-cause mortality and cardiovascular events and undertake subsequent analyses of the models for hypothesis generation in the context of MLTC. At the onset, the focus will be to develop robust AI models for prediction as compared to established benchmarks. The focus will then shift to explainability and association studies.

The researcher is expected to take ownership of the project, propose novel methods, models and applications of ML/DL, write protocols for studies, present the ideas within the group, have advanced coding and data processing skills to execute the ideas in a timely manner and publish the results in high impact ML conferences and medical journals such as ICML, NeurIPS, Lancet, JAMA, BMJ, and Nature Machine Intelligence. As a senior researcher the holder of the position is expected work with other senior researchers within the team and lead grant applications on related topics. 

The suitable candidate must hold a minimum of PhD or an equivalent qualification in computer science, statistics, mathematics, engineering or other relevant areas and have up-to-date knowledge in advanced AI topics, such as deep learning, representation learning, sequence models, NLP, multimodal AI, generative models. The researcher must have advanced programming skills in Python and related data processing, machine learning, deep learning, and visualisation libraries, such as PyTorch, TensorFlow, scikit-learn, Dask, PySpark, Pandas and have familiarity with causal inference on observational data. 

The post is full-time (part-time will be considered, a minimum of 0.6 FTE) and is fixed term for 24 months in the first instance. Applications for flexible working arrangements are welcomed and will be considered in line with business needs. 

The closing date for applications is 12.00 noon on Monday 1st April 2024.