Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Curtin University
- SciLifeLab
- Nature Careers
- Technical University of Denmark
- DAAD
- NTNU - Norwegian University of Science and Technology
- Technical University of Munich
- ; University of Leeds
- ; University of Warwick
- Cranfield University
- Humboldt-Stiftung Foundation
- CWI
- Chalmers University of Technology
- Leibniz
- Monash University
- RMIT University
- Swinburne University of Technology
- University of Twente
- ;
- ; Durham University
- ; Manchester Metropolitan University
- ; Swansea University
- ; University of Exeter
- Aalborg University
- Ariel University
- Brookhaven Lab
- Canadian Association for Neuroscience
- Claremont Graduate University
- Cornell University
- Deutsches Elektronen-Synchrotron DESY •
- ETH Zurich
- Fraunhofer-Gesellschaft
- Ghent University
- Hannover Medical School •
- Imperial College London
- Karlsruhe Institute of Technology •
- Linköping University
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Sustainable Materials •
- McGill University
- Mälardalen University
- National Research Council Canada
- Pennsylvania State University
- Queensland University of Technology
- Technische Universität Berlin •
- Umeå University
- University of Copenhagen
- University of Lethbridge
- University of Minnesota
- University of Utah
- Universität Hamburg •
- VIB
- Østfold University College
- 46 more »
- « less
-
Field
-
information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image processing
-
and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
-
velocity changes at selected locations with the introduction of unsupervised machine learning and study the interaction of mass balance changes (crustal stress changes) and geohazards such as rain-induced
-
optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
-
and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets
-
Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
-
relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
-
control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
-
nomination Continue nomination The selection procedure Icon Applicants Applicants Icon Foundation Foundation Icon Notification Notification Nomination Examinationapprox. 1-2 months Review Processapprox
-
Engineering or any other related field. You must meet the requirements to access and perform research on dual-use technologies according to Norwegian regulations on Control of the Export of Strategic Goods