National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

T&R Lecturer in Health Data Sciences

The University of Manchester
Manchester
4 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist - UK 12 Month FTC

Research Scientist

Machine Learning Research Engineer

Head of IWR Data Engineering and Enablement

Data Scientist

Senior Data Science Developer

The Division of Informatics, Imaging and Data Sciences in the School of Health Sciences wishes to recruit an enthusiastic and innovative individual to the role of Lecturer in Health Data Science to grow our ambitious portfolio of research and training. This role will work across our division with other academics and will be encouraged to attract research funding from various sources to build their own team. You will deliver new teaching opportunities for postgraduate students and supervisor/mentor PhD students.

You will join an engaged digital health community at Manchester with over 100 in The Division of Informatics, Imaging and Data Sciences, and plug-in to our network of over 400 who work across the University in different disciplines allied to the Division including The Pankhurst Institute, Biomedical Research Centre (BRC) and Applied Research Collaboration (ARC). What makes us truly unique at Manchester is our close coupling between researchers, software engineers, clinicians, methodologists and end users/patients, drawing on strength from each to solve real-world problems. This virtuous circle allow us to continually develop a rich and innovative research and software agenda, and it is this inter-disciplinary and team approach that is a distinctive feature when working at Manchester. In the Division of Informatics, Imaging and Data Sciences we also deliver the UKs first and largest MSc in Health Data Science as well as a joint MSc in Health Informatics in partnership with UCL, and a PGCert in Clinical Data Science. We also have a thriving postgraduate research international community.

In the Division, we have a strong reputation of providing a caring inter-disciplinary team environment with wide access to data resources and UK and international networks of expertise. We have a strong ethos of career development and are extremely proud to provide a supportive and flexible working environment for staff from different backgrounds and with different identities.

We are strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. An appointment will always be made on merit. For further information, please visit:https://www .bmh.manchester.ac.uk/about/equality/

Interviews for this role will take place on 04 July 2025.

What you will get in return:

  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers

As an equal opportunities employer we support an inclusive working environment and welcome applicants from all sections of the community regardless of age, disability, ethnicity, gender, gender expression, religion or belief, sex, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working you can find out morehere

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any CV’s submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Professor Georgina Moulton

Email:

General enquiries:

Email:

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.

Please be aware that due to the number of applications we are unfortunately not able to provide individual feedback on your application.


National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.