Sort by
Refine Your Search
-
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
-
, contributing to our development and the success of our mission. The core responsibility of this role is the development of multiscale computational models, with particular emphasis on bio-based composite
-
neural network models, produce stimuli for artificial and biological agents, participate in experiments with chicks maintained in the Biological Services Unit, contribute to lab meetings and research
-
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
-
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
-
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
-
Research Council’s (AHRC) Bridging Responsibilities AI Divides (BRAID) programme that will explore new technologies, new business models and new approaches to data provenance in pursuit of an equitable
-
)genetic perturbations and mouse in vivo models to investigate the contributions of tissue-specific gene regulation and non-coding GWAS signals to cardiac traits and diseases (Frost et al bioRxiv 2025, Parey
-
About the Role We have been funded by Alzheimer’s Society led by Prof Nathan Davies to evaluate hospital at home services/care models for people living with dementia. The role will lead the study
-
, modelling and simulation, CFD, control and experimental investigation would be particularly useful. Candidates close to completion of their PhD will initially be appointed in the junior research training zone