Overview
We are seeking ambitious 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.
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
Responsibilities
* Collaborate with a multidisciplinary team to apply AI methods to health data and translational medicine challenges.
* Contribute to research on foundation models, multimodal deep learning, generative AI methods, transformer architectures, and causal inference for longitudinal health data analysis.
* Work with Python and R for healthcare analytics; use ML/DL frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn.
* Engage with real-world clinical datasets, medical imaging, digital pathology, or multi-omics data; understand healthcare data standards (FHIR, SNOMED-CT, ICD-10) and data protection requirements (GDPR, NHS Data Security Standards).
* Experience with cloud computing platforms (Azure, AWS) for large-scale health data processing is advantageous.
* Pursue a developing publication profile in health informatics or medical AI journals and conferences; collaborate with clinicians and healthcare professionals.
* Understand the UK healthcare system, clinical workflows, and regulatory frameworks for AI in healthcare.
Qualifications
* PhD (or nearing completion) in computer science, biomedical engineering, computational medicine, machine learning, or biomedical data science, with strong foundation in at least one area: computer vision, computational imaging, computational biomechanics, applied mathematics and statistical modelling.
* Proficiency in advanced AI techniques including foundation models, multimodal deep learning, generative AI methods, transformer architectures, and causal inference for longitudinal health data analysis.
* Experience with Python and R for healthcare analytics; familiarity with ML/DL frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn.
* Experience with real-world clinical datasets, medical imaging, digital pathology, or multi-omics data is highly valued.
* Knowledge of healthcare data standards (FHIR, SNOMED-CT, ICD-10) and data protection requirements (GDPR, NHS Data Security Standards).
* Experience with cloud computing platforms (Azure, AWS) for large-scale health data processing is advantageous.
* A developing publication profile in health informatics or medical AI; ability to work in interdisciplinary settings.
* Understanding of the UK healthcare system, clinical workflows, and regulatory frameworks for AI in healthcare is valuable.
Additional information
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
Note: This vacancy will close for applications at midnight on the closing date. See the Further Particulars document for the person specification criteria.
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