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Research Fellow in Computational Fluid Dynamics and Machine Learning - Predicting Aerosol Droplets Dispersion in Indoor Spaces


Job details
  • UCL Eastman Dental Institute
  • London
  • 1 week ago

About the role

The post will underpin our activities in computational flow analysis focusing on aerosol droplet dispersion. We will be undertaking computational modelling of aerosol dispersion due to human breathing, towards understanding transmission risk of airborne diseases in hospital spaces. The modelling will be conducted for various clinical settings, first using computational fluid dynamics (CFD) which will then be accelerated using machine learning (ML), including physics-informed ML algorithms. The model-based predictions will be complemented by experimental measurements of aerosol dispersion, conducted by other project members. Our ultimate goal is to provide a tool for healthcare professionals to predict aerosol dispersion and impact of mitigations such as portable air purifiers.

About you

We would be delighted to receive applications from candidates who meet the following criteria:

Holder of a PhD in fluid mechanics and/or related areas coupled with an excellent track record of research in computational fluid dynamics and/or physics-informed machine learning Track record of excellent publications. Interest in engaging in some department teaching activities. Excellent communication skills. Commitment to contribute to periodical research progress reports and presentations as part of the project deliverables Ability to take initiatives and engage in challenging cross-disciplinary research Enthusiasm to contribute to generation of new ideas to improve patient safety Commitment to contribute to periodical research progress reports and presentations as part of the project deliverables Ability to take initiatives and engage in challenging cross-disciplinary research Enthusiasm to contribute to generation of new ideas to improve patient safety

Please refer to the attached Job Description & Person Specification for a comprehensive list of the skills and attributes required.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:

41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days Additional 5 days’ annual leave purchase scheme Defined benefit career average revalued earnings pension scheme (CARE) Cycle to work scheme and season ticket loan Immigration loan Relocation scheme for certain posts On-Site nursery On-site gym Enhanced maternity, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance

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