Research Assistant/Associate in Digital health

Salary: Reserach Assistant - £33,002 to £34,610 per annum

Research Associate - £35,608 per annum

Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package; plus the opportunity to buy more, great pension schemes and a number of health and wellbeing initiatives to support you.

Closing Date: 05 February 2026

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

The project is funded through the UKRI EPSRC “Transforming the Objective Real-world measUrement of Symptoms (TORUS)” research programme in collaboration with Prof Ian Craddock & team at the University of Bristol. A cure for Parkinson's disease has been held back for decades by the extreme difficulty of measuring whether proposed new drugs actually improve the patient's symptoms and daily life. TORUS aims to solve that problem through a novel platform of sensing technologies for use in patients' own homes along with an advanced data fusion and machine learning pipeline that measures changes in specific mobility-related behaviours over weeks and months.

The vision of TORUS is to create the capability to autonomously, continuously and objectively measure symptoms of illness (mobility-related activities of daily living) many times every day during the clinical trial of a new drug, in the patient's own home and for months at a time. TORUS will achieve this goal by using a wrist-worn wearable integrated synergistically with AI-enabled cameras, led by codesign to ensure that decisions taken in TORUS reflect the views and priorities of diverse patients & families. This 5-year programme grant has been funded over £6M from the EPSRC and is a collaboration between the University of Bristol and Newcastle University.

The work will be undertaken within the Brain and Movement (BAM) Research Group based at the Translational and Clinical Research Institute with Dr Silvia Del Din, Prof Lynn Rocheste and Prof Paul Watson frm the School of Computing..

It will be based in the Translational and Clinical Research Institute, it will focus on the application of advanced machine learning methods and analytics on wearable technology data to measure digital outcomes, including mobility and fatigue, in people with Parkinson’s

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

For informal enquiries contact: Dr Silvia Del Din ([email protected]) and/or Prof Paul Watson ([email protected]) and/or Prof Lynn Rochester ([email protected]).

Weblinks

Brain and Movement Research Team: https://research.ncl.ac.uk/bam/

Clinical Ageing Research Unit: https://www.newcastlebrc.nihr.ac.uk/research/research-infrastructure/clinical-ageing-research-unit-caru/

Biomedical Research Centre – Digital Health, Ageing Innovation and Inclusion theme: https://www.newcastlebrc.nihr.ac.uk/digital-health-ageing-innovation-and-inclusion/

Translational and Clinical Research Institute: https://www.ncl.ac.uk/medical-sciences/research/institutes/translational/

Find out more about the Faculty of Medical Sciences here: https://www.ncl.ac.uk/medical-sciences/

Find out more about our Research Institutes here: https://www.ncl.ac.uk/medical-sciences/research/institutes/

As part of our commitment to career development for research colleagues, the University has developed 3 levels of research role profiles. These profiles set out firstly the generic competences and responsibilities expected of role holders at each level and secondly the general qualifications and experiences needed for entry at a particular level.

To apply, please complete an online application and upload a CV and a cover letter. Your cover letter should be a detailed supporting statement outlining why you are a good fit for the role. Please explain how you meet the essential criteria outlined and evidence this with examples.

Key Accountabilities

Although working under the general guidance of an academic or Principal Investigator, the postholders will contribute ideas, including enhancements to the technical or methodological aspects of their studies, thus providing substantial 'added value' Develop and carry out the specified project using appropriate techniques and equipment as outlined in the personal requirements Determine appropriate methodologies for research, with advice and support where required Contribute to grant applications submitted by others and in time develop own research objectives and proposals for funding Begin to write, with appropriate support, proposals for individual research funding or, where funders do not permit this, contribute to the writing of collective bids Assess research findings for the need/scope for further investigations Contribute to the writing up of their research for publication and dissemination, either through seminar and conference presentations or through publications Present research findings, either at conferences or through publications in reputable outlets appropriate to the discipline May be involved in the supervision, with guidance, of final year undergraduate research projects and in providing support to postgraduate research students or Research Assistants Will need to work with the support staff and, on occasions, with undergraduate and postgraduate students, and interact intellectually with other academic members of the Institute. May contribute to events celebrating the public engagement of science/social sciences/humanities Develop an awareness of University structures, policies and procedures and relevant issues in the higher education, research, social and political environment

The Person

Knowledge, Skills and Experience (Essential)

Ability to work well as part of a team and rapidly acquire new skills Detailed subject knowledge in the area of research, specifically of digital health applications and machine learning techniques applied for mobility and fatigue quantification Likelihood of advanced skills directly related to the research projects High level of analytical and problem-solving capability Ability to communicate complex information with clarity and to encourage the commitment of others Experience of research with clear transferable skills and some experience or awareness of the research environment Presentations at conferences and/or high-quality publications Expertise working with wearable technology data and analysis Experience in machine learning/ AI techniques Experience with signal processing and Application (App) development (especially as applied to mobility and fatigue estimation) Expertise in developing novel algorithms, but also understanding, optimising and applying developed algorithms for extraction of digital mobility outcomes (e.g. gait outcomes) Very good knowledge of and experience using Matlab or equivalent programming languages (e.g. R, Python) Database and project management skills Knowledge of statistical techniques

Knowledge, Skills and Experience (Desirable)

Good information technology and computing skills and experience with cloud computing platforms Experience working with older adults and/or patient groups. Understanding of neurodegenerative conditions, including Parkinson’s disease. Experience with PPIE activities

Attributes and Behaviour

Ability to work independently and as part of a team. Capacity for original thought.

Qualifications

Good honours degree (or equivalent) with some subject knowledge in Biomedical Engineering, Computer Science or related field (Research Assistant) A PhD in Biomedical Engineering, Computer Science or related field (Research Associate)

Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.

We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.

At Newcastle University we hold a Gold Athena Swan award in recognition of our good employment practices for the advancement of gender equality. We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a Disability Confident employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.

In addition, we are a member of the Euraxess initiative supporting researchers in Europe.

Requisition ID: 29033