Postdoctoral Research Assistant in Machine Learning

University of Oxford

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. This prestigious research position is funded by Novo Nordisk and is part of an ambitious consortium of academic and industrial collaborators with world-leading expertise in machine learning and in-silico trials. 

The role will provide a unique opportunity to perform cutting-edge machine learning research in health, be challenged and grow in a multi-disciplinary environment, and develop a high-profile academic career by taking a leadership role while working alongside other junior and senior researchers within Deep Medicine and proactively collaborating with other project leads and researchers from the Department of Engineering, Department of Computer Science and Novo Nordisk.

The researcher will be expected to lead, build upon and advance this work to identify clusters of heart failure patients that show distinct trajectories, respond differently to treatments, and translate into clinically verifiable subtypes. Working with some of the largest and most comprehensive EHR, in the world, specifically CPRD and UK Biobank, 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 researcher is expected to take ownership of the project, propose novel methods, models and applications of ML/DL for identification of heart failure subtypes, 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, European Heart Journal 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 advanced knowledge in DL and a strong background in statistics. Familiarity with causal inference on observational data and prior related experience is preferred. A strong foundation and up-to-date knowledge in advanced AI topics, such as deep learning, representation learning, sequence models, NLP, multimodal AI, generative models and 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 are also essential for this role. Please see the job description for an extensive list of essential criteria. 

The post is full-time (part-time will be considered, a minimum of 0.8 FTE) and is fixed term for 15 months in the first instance. Applications for flexible working arrangements are welcomed and will be considered in line with business needs.

You will be required to upload a CV and Supporting Statement as part of your online application. Click here for information and advice on writing an effective

Supporting Statement

The closing date for applications is 12.00 noon on Monday 19 June 2023.

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