"Research Assistant/Associate"

Newcastle University

Location: Newcastle upon Tyne

Salary: £33,002 to £35,608 per annum. See advert text for details.

Hours: Full Time

Contract Type: Fixed-Term/Contract

Placed On: 22nd January 2026

Closes: 5th February 2026

Job Ref: 29033

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Salary
Research Assistant - £33,002 to £34,610 per annum.
Research Associate - £35,608 per annum.

The Role
This is a full-time, 2.5-year fixed-term Research Assistant/Associate position and provides an exciting opportunity for an early career scientist who is interested in wearable technology and novel machine learning techniques applied to digital outcomes of mobility and fatigue.

You will be expected to work in an interdisciplinary group who has an established international reputation in mobility analysis, digital health outcomes and wearable technology advanced analytics.

This post will involve collecting wearable technology data, implementing novel machine learning advanced analytics for processing and validation of data pertaining to mobility, motor symptoms/function, activity and fatigue, managing complex datasets and collaborate with researchers in partner institutions (e.g., University of Bristol) to publish and present key findings from the projects.

Your role will include:

• Manage workflow within the project for data management.
• Collaborate and communicate with project partners.
• Collect clinical, mobility and motor function data in laboratory, home-like and real-world environments.
• Implement novel advanced machine learning methods (e.g., federated learning techniques).
• Apply existing algorithms, develop and implement new signal processing techniques and algorithms to extract relevant digital outcomes pertaining to mobility, motor symptoms/function, activity patterns and fatigue in a variety of participant cohorts (e.g., older adults, people with Parkinson’s disease).
• Perform statistical analysis and manage complex datasets.
• Prepare reports.
• Publish papers and present findings and results.

This post is fixed-term for a period of 2.5 YEARS.

For informal enquiries contact: Dr Silvia Del Din and/or Prof Paul Watson and/or Prof Lynn Rochester.