Applications are invited for the position of Senior Research Associate to join “GEM” (Generalized Epidemic Modelling), an exciting new project funded by the Wellcome Trust, which is developing a domain-specific modelling language (DSML) implementing statistical analysis and forecasting for epidemics. We are aiming to provide a software environment for rapid development of real-time epidemic models, with cutting-edge machine learning implementations to improve the speed at which the epidemiological community can respond to new outbreak threats. In particular, we wish to provide these techniques to the epidemiological community through a clean, concise DSML with interfaces in Python and R.
You will have a high level of competency in Python programming, with experience of R and C++ being desirable. You must have experience of software development for data science applications, and have a strong commitment to open source and collaborative software development principles, particularly agile coding and distributed version control. As we are developing a DSML, experience of computer language design and interpretation is also desirable, though not mandatory. Knowledge of probabilistic dynamical modelling techniques would likewise be desirable for this post.
The GEM project represents a new digital health collaboration between Lancaster Medical School, the School of Computing and Communications, and the Department of Mathematics and Statistics, brought together by Lancaster University’s Data Science Institute. The post will be based in Lancaster Medical School within CHICAS, a research group of 10 academic staff members actively engaged research at the interface of health informatics, computing, and statistics. Furthermore, as part of the Data Science Institute, this project offers opportunities to engage in career development in research, leadership, and teaching skills across the Lancaster University campus.
The Faculty provides an environment that strongly supports the individual needs of each employee, promoting a healthy work-life balance. We are committed to family-friendly and flexible working policies on an individual basis, as well as the Athena SWAN Charter, which recognises and celebrates good employment practice undertaken to address gender equality in higher education.
Part-time/job share/flexible working options will be considered for this position. This is a one year fixed term position.
Informal enquiries to Dr Chris Jewell (c.jewell@lancaster.ac.uk, CHICAS), Prof Peter Neal (p.neal@lancaster.ac.uk, Mathematics and Statistics), Dr Zheng Wang (z.wang@lancaster.ac.uk, Computing and Communications) or Prof Jo Knight (j.knight1@lancaster.ac.uk, CHICAS & Data Science Institute).
Lancaster Data Science Institute: www.lancaster.ac.uk/dsi/
We welcome applications from people in all diversity groups.
Closing Date: 11 Apr 2019
Category: Research
