Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Swansea University
- University of Oxford
- University of Manchester
- Swansea University;
- Newcastle University
- ;
- Cardiff University
- KINGS COLLEGE LONDON
- UNIVERSITY OF SURREY
- City University London
- University of Greenwich
- University of Leicester
- University of Greater Manchester;
- University of London
- Aston University
- City St George’s, University of London;
- Durham University
- Edinburgh Napier University;
- King's College London
- Manchester Metropolitan University
- Queen Mary University of London;
- Queen's University Belfast
- University of Bath
- University of Bath;
- University of East Anglia;
- University of Hertfordshire;
- University of Leicester;
- University of Newcastle
- University of Oxford;
- University of Sheffield
- University of Sheffield;
- University of Strathclyde;
- University of West London
- University of York;
- 24 more »
- « less
-
Field
-
noise-resilient and fault-tolerant quantum computation. The project will involve developing novel theoretical frameworks, designing new error suppression schemes, and validating them through numerical
-
component (e.g., a postgraduate dissertation) and have a strong grasp of computational and statistical methods. You will also have excellent communication skills. This is post is part-time (0.50 FTE), fixed
-
applications that are interested in pursuing interdisciplinary projects incorporating elements of computational science methodologies in the context of social science challenges spanning the remits of the UK
-
22 Oct 2025 Job Information Organisation/Company Swansea University Department Central Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country
-
job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number RS898 Is the Job related to staff position within a Research Infrastructure? No Offer Description
-
-conditioning and recovery, parenting, biomechanics, nutrition, choking under pressure, genetics, and numerous other topics which all play an important role in achieving high levels of performance. Exercise
-
methodologies, from observational to computational and population-level modelling. Such projects and associated methods are made possible through the linkage of administrative and health data, increasing demand
-
of computational fluid dynamics 3. Knowledge of two-phase flow modelling approaches, such as flows with interfaces based on Volume of Fluid method or similar 4. A sound knowledge of the English language, both oral
-
, Physics, or a related field. Experience with quantum chemical methods and high-performance computing is essential, alongside strong analytical and problem-solving skills. Evidence of contributions to open
-
multisource blending methods will then be applied (e.g. kriging, probabilistic merging, machine learning) to combine datasets and preserve extremes. Uncertainty will be quantified explicitly, with outputs