Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Forschungszentrum Jülich
- Nature Careers
- Delft University of Technology (TU Delft)
- Technical University of Denmark
- Technical University of Munich
- CNRS
- Cranfield University
- DAAD
- NTNU - Norwegian University of Science and Technology
- University of Luxembourg
- Eindhoven University of Technology (TU/e)
- Susquehanna International Group
- University of Southern Denmark
- Leiden University
- Delft University of Technology (TU Delft); yesterday published
- NTNU Norwegian University of Science and Technology
- Newcastle University
- University of Nottingham
- ETH Zürich
- University of Exeter
- Aalborg University
- Imperial College London;
- Utrecht University
- Erasmus University Rotterdam
- KU LEUVEN
- Leibniz
- Tallinn University of Technology
- University of Exeter;
- Uppsala universitet
- Delft University of Technology (TU Delft); Published yesterday
- Empa
- Fraunhofer-Gesellschaft
- Linköpings universitet
- Norwegian University of Life Sciences (NMBU)
- Swansea University
- University of Amsterdam (UvA)
- University of Birmingham;
- AALTO UNIVERSITY
- Delft University of Technology (TU Delft); Delft
- Duke University
- Heidelberg University
- La Trobe University
- Loughborough University
- Maastricht University (UM)
- Manchester Metropolitan University;
- Radboud University
- The University of Manchester
- Umeå University
- University of Cambridge
- University of East Anglia
- University of Southern Queensland
- University of Surrey
- Vrije Universiteit Amsterdam (VU)
- Vrije Universiteit Brussel
- AMOLF
- Aalborg Universitet
- Aarhus University
- Academic Europe
- Carnegie Mellon University
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Curtin University
- Delft University of Technology (TU Delft); today published
- Edinburgh Napier University;
- European Magnetism Association EMA
- HONG KONG BAPTIST UNIVERSITY
- Helmholtz-Zentrum Geesthacht
- Helmholtz-Zentrum Hereon
- ICN2
- ISCTE - Instituto Universitário de Lisboa
- Leiden University; today published
- Linkopings universitet
- Linköping University
- Luxembourg Institute of Science and Technology
- Maastricht University (UM); yesterday published
- Murdoch University
- Mälardalen University
- Radboud University Medical Center (Radboudumc)
- Swansea University;
- The Ohio State University
- The University of Edinburgh;
- UNIVERSITY OF HELSINKI
- UiT The Arctic University of Norway
- Umeå universitet
- Universidade de Coimbra
- University Medical Center Utrecht (UMC Utrecht)
- University of Adelaide
- University of Amsterdam (UvA); Published today
- University of Amsterdam (UvA); yesterday published
- University of Birmingham
- University of Bradford;
- University of Cambridge;
- University of East Anglia;
- University of Massachusetts Medical School
- University of Nottingham;
- University of Plymouth
- University of Regensburg
- University of Sheffield
- University of Twente
- University of Twente (UT)
- University of Warwick
- 90 more »
- « less
-
Field
-
project, you will develop machine learning models that learn from high-throughput experimental datasets to uncover structure–property relationships and guide the selection of new experiments. The datasets
-
develop models that can read, extract and acquire knowledge from legacy data, coming both in the form of text and in the form of structured data (e.g. physical measurements) to predict characteristics
-
Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
-
and a heterogeneous emerging computer architecture, collaborate regarding compiler and other tools as well as modeling their hardware for integration into the emerging computer architecture framework
-
, or a related field. Have documented experience in some of the following: Computational materials modelling or quantum mechanical simulations (e.g. DFT, MD). Machine learning / deep learning (preferably
-
Learning for Foundation Models’, where the aim is to adapt these models to new tasks without forgetting previous knowledge. The precise focus of the project can be defined in collaboration with
-
We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
-
to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
-
FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
-
programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key