Research Associate in Digital Health

The role

The UK faces a care crisis where older people and people with disabilities who lose independence may not have the care they need. This will have a major negative impact on the welfare of citizens and the UK economy. The practical solution to this urgent healthcare need is through technologies that directly address the mobility and independence needs of this population precisely where it is needed – on their bodies, in their homes and in the community and environments where they live and socialise. VIVO will deliver new world class research and translation capability for the study, maintenance and restoration of mobility and independence in older people and people with disabilities. It will develop the critically needed technology infrastructure across smart materials and actuation, control and bio-interfacing, digital-health monitoring and machine learning, and will co-develop with users and stakeholders in-home, on-body and away-from-home digital physical assistance devices to enhance and restore independence, close the loop between digital monitoring and personalised intervention, reduce costs, and improve quality of life.

What will you be doing?

The successful applicant will:  

• Perform fundamental and applied research, within the VIVO digital health monitoring and interventional analysis team, in the key area of human-behaviour analysis using spatiotemporal data from different sources and modalities.
• Contribute to the design of the VIVO assistive devices, including planning data collection activities with patients.
• Contribute to publishing the work in top journals and international conferences.
• Present the work in seminars and workshops.
• Attend regular project meetings.
• Prepare progress reports for the VIVO management team and advisory board.
• Advise on and participate in deployment activities related to the VIVO systems.

You should apply if

Essential

• PhD in machine learning, data science, AI or related research area or be working towards one.
• Excellent and broad conceptual and practical knowledge of the state-of-the-art in machine learning and data science.
• Demonstrably excellent software development skills with Python and relevant libraries (scikit-learn, PyTorch/TensorFlow, and others).
• Proven deep understanding of and demonstrable skills in data-driven experiments and performance evaluation.
• Excellent communication and presentation skills.
• Proven ability to work both independently and as part of a team (VIVO is a very large project and team working will be a daily activity).
• Proven ability to plan, manage and prioritise own workload while responding to the changing priorities and needs of a busy, dynamic environment.

Desirable     

• Track record in time series analysis/activity recognition for healthcare.
• Interest in health applications of data science.
• First or co-authored publications on relevant topics in top-tier international conferences and workshops.
• Ability to communicate with healthcare professionals, presenting technical information in an understandable way.

Additional information

For informal queries, please contact: Telmo de Menezes e Silva Filho, telmo.silvafilho@bristol.ac.uk

For informal queries please contact:

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/

Contract type: Open ended with fixed funding until 01/12/2029

This advert will close at 23:59 UK time on 19/03/2025

Interviews are anticipated to take place on 8th April 2025

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