Research Associate in AI for Multimodal Healthcare Data

We are seeking Postdoctoral Research Associates who are passionate about foundation models, multimodal AI, and longitudinal health and care data to join our world-leading multidisciplinary team at the NIHR Manchester Biomedical Research Centre Digital Infrastructure. You will collaborate with experts in computational medicine, clinical informatics, and translational healthcare, working at the cutting edge of AI innovation in medicine.

This is an extraordinary opportunity to apply your expertise to large-scale population health datasets, including UK Biobank, clinical trials data, and real-world data from across Greater Manchester's integrated care system and the North West Secure Data Environment, making a transformative impact in precision medicine, cardiovascular health, cancer research, and respiratory medicine.

Applicants should have a PhD (or nearing completion) in computer science, biomedical engineering, computational medicine, machine learning, or biomedical data science, with a strong foundation in at least one of the following areas: computer vision, computational imaging, computational biomechanics, applied mathematics and statistical modelling, focusing on algorithm design and clinical data analysis.

Proficiency in advanced AI techniques will be essential, including foundation models, multimodal deep learning, generative AI methods, transformer architectures, and causal inference approaches for longitudinal health data analysis, as well as expertise in Python and R for healthcare analytics, and experience with ML/DL frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn.

Experience working with real-world clinical datasets, medical imaging, digital pathology, or multi-omics data will be highly valued, along with an understanding of healthcare data standards (FHIR, SNOMED-CT, ICD-10) and clinical research methodologies. Knowledge of data protection requirements in healthcare settings (GDPR, NHS Data Security Standards) and experience with cloud computing platforms (Azure, AWS) for large-scale health data processing will be advantageous.

A developing publication profile in health informatics or medical AI journals and conferences will strengthen your application, as will experience in interdisciplinary collaboration with clinicians and healthcare professionals. A thorough understanding of the UK healthcare system, clinical workflows, and regulatory frameworks for AI in healthcare will be particularly valuable for this role.

Informal enquiries can be made to Prof Alejandro Frangi. Email: alejandro.frangi@manchester.ac.uk and Dr Stuart Grant stuart.grant@manchester.ac.uk

As this role involves research at a postgraduate level, applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI.

Enquiries about the vacancy, shortlisting and interviews:

Name: Alex Frangi

Email: alejandro.frangi@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

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

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

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