Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- DAAD
- Technical University of Denmark
- Technical University of Munich
- Cranfield University
- University of Luxembourg
- Forschungszentrum Jülich
- ;
- Curtin University
- Linköping University
- Susquehanna International Group
- University of Southern Denmark
- Ghent University
- NTNU - Norwegian University of Science and Technology
- University of Nottingham
- CNRS
- Chalmers University of Technology
- Leibniz
- University of Bergen
- University of Groningen
- University of Tübingen
- ; City St George’s, University of London
- ; The University of Manchester
- CWI
- Leiden University
- Ludwig-Maximilians-Universität München •
- Monash University
- University of Basel
- VIB
- ; University of Exeter
- ; University of Nottingham
- La Trobe University
- Lulea University of Technology
- University of Adelaide
- University of Antwerp
- University of Twente
- University of Twente (UT)
- ; Swansea University
- AALTO UNIVERSITY
- Delft University of Technology (TU Delft)
- Hannover Medical School •
- Queensland University of Technology
- Radboud University
- The University of Manchester
- University of Göttingen •
- University of Southern Queensland
- Uppsala universitet
- Vrije Universiteit Brussel
- ; University of Southampton
- ; University of Surrey
- Aalborg University
- Aarhus University
- Abertay University
- Brandenburg University of Technology Cottbus-Senftenberg •
- Carnegie Mellon University
- Delft University of Technology (TU Delft); Delft
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- GFZ Helmholtz Centre for Geosciences
- Humboldt-Stiftung Foundation
- KINGS COLLEGE LONDON
- Leiden University; Leiden
- Murdoch University
- Radix Trading LLC
- SciLifeLab
- Swedish University of Agricultural Sciences
- Swinburne University of Technology
- Technische Universität Berlin •
- The University of Chicago
- UNIVERSITY OF HELSINKI
- Umeå University
- Universite de Moncton
- University of Bristol
- University of Cambridge
- University of Cambridge;
- University of Copenhagen
- University of Minnesota
- University of Münster •
- University of Newcastle
- Université Laval
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- Wageningen University and Research Center
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Durham University
- ; Newcastle University
- ; Technical University of Denmark
- ; The University of Edinburgh
- ; UCL
- ; UWE, Bristol
- ; University of Birmingham
- ; University of Bristol
- ; University of Greenwich
- ; University of Leeds
- ; University of Oxford
- ; University of Reading
- ; University of Warwick
- 89 more »
- « less
-
Field
- Computer Science
- Engineering
- Biology
- Mathematics
- Medical Sciences
- Economics
- Linguistics
- Materials Science
- Chemistry
- Humanities
- Science
- Environment
- Electrical Engineering
- Design
- Education
- Arts and Literature
- Business
- Earth Sciences
- Physics
- Social Sciences
- Psychology
- Sports and Recreation
- 12 more »
- « less
-
materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
-
Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
-
fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
-
The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
-
limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data. You will work at the frontier of active learning and ML-guided
-
synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
-
to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
-
engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record