Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- ;
- Durham University
- University of London
- DURHAM UNIVERSITY
- King's College London
- University of Liverpool
- Aston University
- Cardiff University
- Heriot Watt University
- Nature Careers
- University of Sheffield
- ; University of Kent
- KINGS COLLEGE LONDON
- Manchester Metropolitan University
- Medical Research Council
- UNIVERSITY OF VIENNA
- University of Cambridge
- 8 more »
- « less
-
Field
-
quantum networks and quantum sensors. Point defects in wide-bandgap solids are an example, where the deterministic interaction between emitted photons and electronic and nuclear spins enables photon
-
on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
-
analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
-
. To address these questions, we combine a series of interdisciplinary approaches ranging from experimental embryology and fluorescent microscopy to mathematical modelling. The lab is highly interdisciplinary
-
in wide-bandgap solids are an example, where the deterministic interaction between emitted photons and electronic and nuclear spins enables photon mediated entanglement for distributed quantum networks
-
manufacturing challenges. The AMMIC team will be undertaking a series of projects with industrial collaborators in the areas of: Materials synthesis (e.g. PVD techniques, Metamaterials, etc.); Digitalisation
-
the long-standing and counterintuitive observation of attraction between similarly charged particles in solution. In a series of papers we described the mechanism behind an “electrosolvation force” that can
-
of attraction between similarly charged particles in solution. In a series of papers we described the mechanism behind an “electrosolvation force” that can drive such an attraction (J Chem Phys 2020, Langmuir
-
of HIV-1 infection by the cellular protein MX2 (MXB), an established innate immune effector. The project builds on a series of virological, molecular genetic, biophysical and structural biology (electron
-
applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a