-
project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
-
data and finite element modelling is a plus. You will have experience in writing publications, and be happy working in a collaborative environment. About the School The role will be based at the School
-
platforms at our prestigious Centre for in vitro Predictive Models (https://www.cpm.qmul.ac.uk/ ), and work with project partners based at the Cross Institute Advanced Tissue Engineering (CREATE) lab
-
potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
-
2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
-
project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
-
with large-scale longitudinal datasets to explore gene–environment interplay and developmental risk pathways. The successful candidate will join a vibrant research team based at Royal Holloway
-
-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
-
About the Role The post is based in the Trauma Sciences Research team within the Centre for Neuroscience, Surgery and Trauma. The Trauma Sciences research team (www.c4ts.qmul.ac.uk) provides
-
(inclusive of London Weighting) based on experience. The successful candidate will be part of the new Centre for Vaccinology and Regenerative Medicine, based on the Hawkshead Campus of the RVC (https