Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- UNIVERSITY OF VIENNA
- University of Oxford;
- KINGS COLLEGE LONDON
- AALTO UNIVERSITY
- King's College London
- Durham University
- ;
- University of Newcastle
- Nature Careers
- Newcastle University;
- Queen Mary University of London;
- UNIVERSITY OF EAST LONDON
- University of Bath
- University of Liverpool
- University of Liverpool;
- Aston University
- Bournemouth University;
- Cardiff University
- Ellison Institute of Technology, Oxford Limited
- European Magnetism Association EMA
- Imperial College London
- Lancaster University
- Lund University
- Royal College of Art
- University of Birmingham
- University of Cambridge;
- University of East London
- University of Glasgow;
- University of Leicester
- VIN UNIVERSITY
- 21 more »
- « less
-
Field
-
developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
-
mission, including through the supervision of undergraduate and graduate student researchers. The post-holder will have the opportunity to teach. Applicants should hold PhD (or close to completion) in
-
effects while building machine-learning-ready kinetic datasets for predictive catalyst design. You should have a PhD (or about to obtain) in Chemistry or field related to this project (Chemical Engineering
-
. About You You will have, or be close to completion of a PhD/DPhil in Statistics, Machine Learning, Data Science, or a related quantitative discipline. You will demonstrate strong specialist knowledge in
-
are seeking a postdoctoral research associate to contribute to an innovative EU Pathfinder project at the intersection of polymer chemistry, molecular dynamics simulations, and machine learning. The primary
-
, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
-
operational practices • Systematically exploring different formulations of mixed-integer constraints in grid optimisation problems • Developing machine learning models to accelerate mixed-integer
-
: 30.04.2032 Reference no.: 5326 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about
-
developing cutting-edge active-learning (Bayesian optimisation) methods that integrate chemical knowledge by capitalising on Large Language Models (LLMs) as well as human knowledge. You should have a PhD in
-
and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game