"Research Associate in Multimodal Generative AI for Virtual Patient Populations in In-Silico Trials"

We are looking for an ambitious Research Associate who is passionate about generative AI, synthetic data, and in-silico trials to join our multidisciplinary team. You will work with colleagues who are experts in cutting-edge image-based multiphysics modelling of cardiovascular fluid dynamics and device-tissue interactions.

You will work with clinical and experimental data to develop innovative geometric deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows for crafting simulation-ready computational anatomy models, incorporating tissue microstructure properties.

This is an exciting opportunity to apply your expertise to large-scale real-world datasets, including clinical trials and population imaging studies, and make a transformative impact in computational modelling and healthcare innovation.

Keywords: Generative AI, synthetic data, in-silico trials, virtual patient cohorts, geometric deep learning, computational anatomy, cardiovascular modelling, multimodal datasets.

What you’ll need: Applicants should have a PhD (or nearing completion) in computational imaging and deep learning, and an understanding of applied mathematics, focusing on algorithm design and analysis. Proficiency in modern ML techniques, including geometric deep learning, diffusion models, and neural networks for multimodal image analysis will be essential, as well as expertise in Python and C/C++ for scientific computing, and in ML/DL frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn. A developing publication profile will be advantageous.

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 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. Hybrid working arrangements may be considered.