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Research Collaborator
4 mesi fa
Title: Research Collaborator (24 months renewable)
Imperial College Business School has partnered with Bocconi University (Milan, Italy) in a European Joint Action on Cardiovascular Disease and Diabetes (JACARDI). As part of this project, a collaboration position is being created. The successful candidates will be employed by Bocconi University and will be based partly at Bocconi and partly at Imperial College London (balance to be determined as a function of project needs and candidates' profiles).
Prospective applicants should apply to Bocconi using the link at the bottom of this advert. Applications made directly to Imperial College are not permitted.
JACARDI, the Joint Action on CARdiovascular diseases and DIabetes is a European Joint Action (JA) funded through the European Commission's EU4Health programme, involving 21 EU countries and 77 partners. Over 4 years, JACARDI aims at reducing the burden of cardiovascular disease and diabetes in EU countries, both at individual and societal level.
The post-holder will join research teams at both Bocconi and Imperial College to lead a critical component of JACARDI, the health and economic evaluation of interventions aimed at preventing and treating cardiovascular disease and diabetes. This will involve the development of Health-GPS, our global microsimulation model, capable of describing non-communicable disease dynamics and estimating the impact of interventions on health and the economy.
While formal employment will be with Bocconi, the appointed candidate will spend a significant proportion of their time in London working with the Centre for Health Economics & Policy Innovation (CHEPI) at Imperial College Business School. Working in London is subject to obtaining an appropriate visa.
Responsibility in the Project:
- Leading the adaptation of Health-GPS enabling the tool to take inputs from individual pilot project sites.
- Supporting the design of pilot project assessments.
- Carrying out simulations utilising Health-GPS to estimate the long-term health and economic outcomes of selected pilot projects.
- Supporting the development of final reports for pilot projects.
Job description:
The candidate will be expected to contribute to the work of a multi-disciplinary research team engaged in the development of a microsimulation model of the future health and economic impacts of health policies. This model (Health-GPS) will be employed in the evaluation of interventions designed to prevent and treat cardiovascular disease and diabetes. In particular, the candidate will be expected to help develop and implement into the existing code base of the model (developed in C++) suitable mathematical algorithms that will reflect the epidemiological and economic dynamics associated with interventions that can modify cardiovascular disease and diabetes risk and outcomes. The position will involve close collaboration with a team of researchers based at Imperial College London, which will require the candidate to be based at Imperial College for at least part of the duration of the appointment.
Application Requirements:
- Master degree in Computer Science, Economics, Epidemiology, or equivalent quantitative degree and/or PhD in Computer Science (preferred), Economics, Epidemiology, or equivalent quantitative degree
- Experience of current and recent C++ releases
- Building and using micro-simulation models to describe disease dynamics
- Working in a multidisciplinary team
For any enquires relating to the Imperial College component of this post, please contact Dr Jack Olney )
External Application URL and instructions below
Application Instructions:
Applicants should apply via our online application system by June 10th, 2024.
The application must include the following documents, which must be attached to the application:
- Professional C.V., in pdf format;
- A list of any titles/qualifications and publications, in pdf format;
- Any certificate, publication, or document that the candidate intends to submit for evaluation, in pdf format.
€50,000 to €70,000 annual gross
