Research Assistant/Associate in Digital health in Newcastle upon Tyne
Research Assistant/Associate in Digital health

Research Assistant/Associate in Digital health in Newcastle upon Tyne

Newcastle upon Tyne Full-Time 30000 - 42000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Join a dynamic team to analyse wearable tech data and apply machine learning for health outcomes.
  • Company: Newcastle University, a leading institution in digital health research.
  • Benefits: Competitive salary, career development, and the chance to make a real-world impact.
  • Why this job: Be at the forefront of digital health innovation and contribute to groundbreaking research.
  • Qualifications: Degree in Biomedical Engineering or Computer Science; experience with machine learning and wearable tech.
  • Other info: Collaborate with top researchers and enjoy a supportive, inclusive work environment.

The predicted salary is between 30000 - 42000 ÂŁ per year.

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 collaborating 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 co-design 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 Translational and Clinical Research Institute with Dr Silvia Del Din, Prof Lynn Rochester and Prof Paul Watson from the School of Computing. 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.

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 award in recognition of our good employment practices for the advancement of gender equality. We also hold a Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are an 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.

Research Assistant/Associate in Digital health in Newcastle upon Tyne employer: Newcastle University

Newcastle University is an exceptional employer, offering a vibrant and inclusive work culture that fosters collaboration and innovation in the field of digital health. With a strong commitment to employee development, you will have access to numerous growth opportunities, including involvement in groundbreaking research projects like TORUS, which aims to revolutionise the measurement of mobility and fatigue in patients with Parkinson's disease. Located in a supportive academic environment, you will be part of a diverse team dedicated to making a meaningful impact on healthcare outcomes.
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Contact Detail:

Newcastle University Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Assistant/Associate in Digital health in Newcastle upon Tyne

✨Tip Number 1

Network like a pro! Reach out to people in the digital health and machine learning fields, especially those connected to the University of Bristol. Attend relevant events or webinars to make connections that could lead to job opportunities.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your work with wearable technology and machine learning. This can be a game-changer when you're chatting with potential employers or collaborators.

✨Tip Number 3

Be proactive! Don’t just wait for job postings; reach out directly to research teams or professors whose work excites you. Express your interest and see if they have any upcoming projects where you could fit in.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Make sure to tailor your CV and cover letter to highlight your experience with mobility analysis and machine learning techniques.

We think you need these skills to ace Research Assistant/Associate in Digital health in Newcastle upon Tyne

Wearable Technology Data Analysis
Machine Learning Techniques
Data Management
Statistical Analysis
Signal Processing
Algorithm Development
Project Management
Communication Skills
Collaboration
Research Publication
Programming in Matlab, R, or Python
Understanding of Neurodegenerative Conditions
Experience with Application Development
Analytical Skills
Problem-Solving Skills

Some tips for your application 🫡

Tailor Your Cover Letter: Make sure your cover letter is not just a generic template. We want to see how your skills and experiences align with the specific requirements of the Research Assistant/Associate role. Highlight your knowledge in digital health and machine learning techniques, and don’t forget to sprinkle in some examples!

Show Off Your Team Spirit: This role is all about collaboration, so let us know how you work well in a team. Share experiences where you’ve successfully collaborated with others, especially in research settings. We love to see candidates who can communicate effectively and bring people together!

Be Specific About Your Skills: When listing your skills, be specific! If you’ve got experience with wearable technology data or machine learning methods, tell us exactly what you did and how it relates to the role. The more detail, the better—we want to see your expertise shine through!

Apply Through Our Website: Don’t forget to apply through our website! It’s the easiest way for us to keep track of your application. Plus, it shows you’re serious about joining our team at StudySmarter. We can’t wait to see what you bring to the table!

How to prepare for a job interview at Newcastle University

✨Know Your Stuff

Make sure you brush up on your knowledge of digital health applications and machine learning techniques. Be ready to discuss how these can be applied to mobility and fatigue quantification, as this will show your genuine interest in the role.

✨Showcase Your Skills

Prepare examples of your experience with wearable technology data and machine learning. Highlight any projects where you've developed algorithms or worked with signal processing, as this will demonstrate your hands-on expertise.

✨Collaboration is Key

Since this role involves working with an interdisciplinary team, think of ways to showcase your teamwork skills. Be ready to discuss past experiences where you collaborated effectively with others, especially in research settings.

✨Ask Thoughtful Questions

Prepare some insightful questions about the TORUS project and its goals. This not only shows your enthusiasm but also your understanding of the challenges faced in measuring mobility-related outcomes in patients with Parkinson’s disease.

Research Assistant/Associate in Digital health in Newcastle upon Tyne
Newcastle University
Location: Newcastle upon Tyne
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  • Research Assistant/Associate in Digital health in Newcastle upon Tyne

    Newcastle upon Tyne
    Full-Time
    30000 - 42000 ÂŁ / year (est.)
  • N

    Newcastle University

    1000-5000
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