(Postdoctoral) Research Assistant in Machine Learning

We invite applications for the position of Research Assistant or Postdoctoral Research Assistant in Machine Learning 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 data-driven health care and precision medicine.

You will be expected to build upon and advance Deep Medicine’s pioneering work on the applications of novel learning paradigms and modelling approaches in machine learning to large-scale, longitudinal UK Electronic Health Records (EHR). The project aims to leverage such methods to identify clusters of patients that show distinct trajectories and might, therefore, respond differently to treatments. Working with some of the largest and most comprehensive EHR in the world, this is a unique opportunity to transfer and apply tools and techniques from machine learning and conduct high-impact research, while contributing to the broader goals of Deep Medicine.

This a prestigious position 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 project aims to push the boundaries of precision medicine in heart failure. This role will provide a unique opportunity to enjoy research in machine learning and health care; grow and be challenged in a multi-disciplinary environment; and create game-changing solutions for health care. It further offers a great opportunity to develop a high-profile academic career, through taking a leadership role in the field of healthcare/biomedical informatics.

You will hold an MSc (PhD/DPhil at grade 7, or near completion) in computer science, statistics, mathematics, engineering or other relevant areas. You will have a strong foundation in advanced AI topics (e.g., Bayesian and probabilistic machine learning, deep learning, sequence models, NLP), up-to-date knowledge about novel paradigms and methods in ML, especially DL, and advanced programming skills in Python (and their related data processing, machine learning, deep learning, and visualisation libraries). You will also have practical experience in preparing data for Machine Learning (e.g., using SQL and/or NoSQL technologies), experience, familiarity, or willingness to learn statistical and epidemiological analysis methods such as survival analysis and hypothesis testing, as well as a proven track record of working in a fast-paced environment and delivering high-quality results against project milestones. Excellent communications skills, the ability to contribute to a multidisciplinary team and the ability to work independently, including decision-making, problem-solving, planning and organisation are also essential for this role.

For an informal discussion about the post, please contact Prof Kazem Rahimi ([email protected]).

This position is full-time and fixed-term for 30 months. This post is available from 1st April 2022. 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: https://www.jobs.ox.ac.uk/cv-and-supporting-statement.

The closing date for applications is 12.00 noon on Monday 6th December 2021. Interviews are expected to take place on Wednesday 15th December 2021.