Sort by
Refine Your Search
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Cornell University
- Utrecht University
- SciLifeLab
- EPFL
- Helmholtz Association of German Research Centres
- King Abdullah University of Science and Technology
- National Energy Technology Laboratory (NETL)
- Umeå University
- Aarhus University
- Chalmers University of Technology
- Institute for bioengineering of Catalonia, IBEC
- Maastricht University (UM)
- THE UNIVERSITY OF HONG KONG
- Texas A&M AgriLife
- University of Luxembourg
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- AALTO UNIVERSITY
- ARCNL
- Aalborg University
- AbbVie
- Bournemouth University;
- Duke University
- Empa
- Erasmus University Rotterdam
- Forschungszentrum Jülich
- Fundació per a la Universitat Oberta de Catalunya
- GFZ Helmholtz-Zentrum für Geoforschung
- Goldsmiths
- Goldsmiths, University of London;
- Harvard University
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Imperial College London
- Karolinska Institutet (KI)
- Leiden University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- National Aeronautics and Space Administration (NASA)
- New York University
- Pennsylvania State University
- RIKEN
- SUNY at Buffalo
- Stanford University
- TTI
- Texas A&M AgriLife Extension
- UNIVERSITY OF EAST LONDON
- Umeå universitet stipendiemodul
- University of Amsterdam (UvA)
- University of Central Florida
- University of East London
- University of Lincoln
- University of Lund
- University of Minnesota
- University of New South Wales
- University of North Carolina at Chapel Hill
- University of Oulu
- University of Vaasa
- University of Vermont
- Wageningen University & Research
- Yale University
- 49 more »
- « less
-
Field
-
-driven mathematical modeling in a transdiagnostic clinical cohort. https://impact-mh.org/awardees/impact-mh/ IMPACT-Y is collecting repeated measures from approximately 2,400 individuals across multiple
-
or neural networks) on CFD data to develop a fast, data-driven wind field predictor. You will combine this surrogate model with AeoLiS and evaluate the accuracy of the new model setup by applying it to
-
capabilities interact with operational conditions, human intervention and the wider maritime and port logistics systems. The postdoctoral researcher will develop data-driven and model-based approaches to support
-
models for complex data, including temporal data. We are interested in both data-driven models as well as models built from synthetic data. Within privacy, we are interested in different types of privacy
-
Postdoc Position in AI Foundation Models for Crop Microbiomes Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
-
community that is driven by its mission, where it will be possible for your work to directly make a difference for society. Benefits Friday afternoons off. Flexibility: our open working model combines remote
-
machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
-
at least one of the following areas: crop modelling, plant sensing or data-driven crop management. Demonstrable experience in translating research insights into practical applications and collaborating with
-
at least one of the following areas: crop modelling, plant sensing or data-driven crop management. Demonstrable experience in translating research insights into practical applications and collaborating with
-
models for multiple chronic diseases in real-world data and cohort studies. To successfully work in this position, experience of data-driven analytical approaches, machine learning and advanced