Location: | London, Hybrid |
---|---|
Salary: | £45,593 to £53,630 per annum |
Hours: | Full Time |
Contract Type: | Permanent |
Placed On: | 26th March 2024 |
---|---|
Closes: | 24th April 2024 |
Job Ref: | MED04485 |
Location: School of Public Health, White City Campus, London
Job Summary
An exciting opportunity to join the EpiEng (Epidemiological Engineering) group led by Dr Kris Parag. We are a multidisciplinary group aiming to discover how principles from data science, mathematics and engineering can inform more realistic epidemic models and improve pandemic prediction and control algorithms at scale. We attempt to probe the limits of what models can achieve and optimise interventions by better understanding the feedback loops and network structures driving transmission.
As a Research Associate in Machine Learning for Complex Epidemics you will devise theory, models and methodology for tracking, forecasting and suppressing infectious disease outbreaks by innovatively adapting algorithms and tools from reinforcement learning, multilayer network theory, causal statistics and complex systems. You will also develop open-access software packages and empirically validate outputs on real, heterogeneous datasets (spatiotemporal case and sequence data).
You will help answer questions about priority diseases (e.g., COVID-19, Ebola virus) and improve preparedness for an unknown Disease X by using machine learning and control theory to: better model poorly understood behavioural drivers of spread, extract salient features of transmission across scales (from individual to population levels) and optimise real-time decision-making from noisy data.
This role is collaborative and ideal for those with strong quantitative skills interested in confronting pandemic modelling challenges. You will engage with top academics at public health, engineering and data science departments at Imperial College and the Universities of Oxford, Cambridge, Hong Kong, Copenhagen and Lund. Experience in epidemiology is not essential. Candidates with varied backgrounds (e.g., physics, artificial intelligence, statistics, engineering or mathematics) are encouraged to apply.
Duties and responsibilities
You will:
Essential requirements
You should possess:
Further Information
The role is full-time and fixed term for 2 years, starting spring or later. Please apply online, including a CV with publications and statement (1-2 pages) on how your skills, and outputs make you suitable.
Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £40,694 - £43,888 per annum.
Flexible working arrangements will be considered. For any queries, please contact k.parag@imperial.ac.uk.
For informal discussion about EpiEng work culture, email Dr Sandor Beregi s.beregi@imperial.ac.uk
Type / Role:
Subject Area(s):
Location(s):