Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Technical University of Munich
- Delft University of Technology (TU Delft)
- Forschungszentrum Jülich
- Cranfield University
- Technical University of Denmark
- NTNU - Norwegian University of Science and Technology
- CNRS
- Newcastle University
- University of Luxembourg
- University of Southern Denmark
- DAAD
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- University of Bergen
- Aalborg University
- Delft University of Technology (TU Delft); yesterday published
- Leiden University
- NTNU Norwegian University of Science and Technology
- University of Nottingham
- Utrecht University
- Swansea University
- University of Exeter
- Imperial College London;
- University of Twente
- University of Twente (UT)
- Erasmus University Rotterdam
- KU LEUVEN
- Leibniz
- Linköping University
- Susquehanna International Group
- Tallinn University of Technology
- University of Exeter;
- Uppsala universitet
- Aalborg Universitet
- Delft University of Technology (TU Delft); Published yesterday
- Empa
- Fraunhofer-Gesellschaft
- Linköpings universitet
- Norwegian University of Life Sciences (NMBU)
- University of Birmingham;
- Vrije Universiteit Amsterdam (VU)
- Duke University
- Heidelberg University
- La Trobe University
- Loughborough University
- Luxembourg Institute of Science and Technology
- Manchester Metropolitan University
- Manchester Metropolitan University;
- The University of Manchester
- Umeå University
- University of Adelaide
- University of Amsterdam (UvA)
- University of Cambridge
- University of East Anglia
- University of Southern Queensland
- Vrije Universiteit Brussel
- AALTO UNIVERSITY
- Aarhus University
- Academic Europe
- Carnegie Mellon University
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Delft University of Technology (TU Delft); today published
- Edinburgh Napier University;
- European Magnetism Association EMA
- Fundació per a la Universitat Oberta de Catalunya
- Grenoble INP - Institute of Engineering
- HONG KONG BAPTIST UNIVERSITY
- Helmholtz-Zentrum Geesthacht
- Helmholtz-Zentrum Hereon
- ICN2
- ISCTE - Instituto Universitário de Lisboa
- Leiden University; today published
- Linkopings universitet
- Maastricht University (UM)
- Maastricht University (UM); yesterday published
- Michigan State University
- Murdoch University
- Swansea University;
- The Ohio State University
- The University of Edinburgh
- The University of Edinburgh;
- The University of Manchester;
- UNIVERSITY OF HELSINKI
- UiT The Arctic University of Norway
- Universidade de Coimbra
- University Medical Center Utrecht (UMC Utrecht)
- 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 Leeds
- University of Massachusetts Medical School
- University of Nottingham;
- University of Plymouth
- University of Regensburg
- University of Sheffield
- University of Surrey
- 90 more »
- « less
-
Field
-
. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
-
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
-
multimodal data, ultimately uniting rigorous machine learning foundations with biological discovery. Project details This PhD project will contribute to the development of generative models for multimodal data
-
catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
-
candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
-
on combining innovative technologies such as remote monitoring, large language models, machine learning, blockchain, and eco-accounting to enhance the efficiency, security, and sustainability of e-bike charging
-
using cutting-edge computational techniques, including machine learning algorithms. Work collaboratively with an interdisciplinary and international team to refine and validate regional wave and ocean
-
PhD Studentships in Statistics, Data Science and Machine Learning Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Overview The
-
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
-
microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments