Research Assistant/Associate in Generative Modelling for Ubiquitous Optical Healthcare Technolo[...]

A position exists for a Research Assistant/Associate in the Department of Engineering, to work on the development of physics informed machine learning methods for healthcare data analysis.

The post holder will be located in West Cambridge, Cambridgeshire, UK.

Responsibilities:

1. Development of approaches to the analysis of data from healthcare technologies.
2. Implementation of complex physics informed machine learning models into the developed healthcare data analysis approaches.
3. Contribution to the supervision of a group of PhD students working on related problems.

Required Skills, Qualifications, and Experience:

• Knowledge of physics informed machine learning approaches suitable for healthcare data analysis.
• Knowledge of the implementation of complex statistical methods.
• Good writing and presentation skills.
• Good verbal and non-verbal communication skills.
• Good time management skills.
• A strong work ethic and a positive attitude are essential.
• Proof of authoring high quality academic publications.

Applicants must have (or be close to obtaining) a PhD in Physics Informed Machine Learning or have equivalent experience. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

Research Assistant: £32,296 - £34,866 Research Associate: £36,924 - £45,163

Fixed-term: The funds for this post are available for 48 months or 30 September 2029, whichever comes soonest.

Please ensure that you upload your Curriculum Vitae (CV) and a covering letter, a publication list and a one-page summary of what you will bring to the role in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

If you have any questions of a technical nature please contact Professor Mark Girolami (mag92@cam.ac.uk) and for queries related to the role or application process, contact Alexandra Roche (div-d-coordinator@eng.cam.ac.uk).

Please quote reference NM44677 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.