Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- CNRS
- Forschungszentrum Jülich
- Leibniz
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Technical University of Munich
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Inria, the French national research institute for the digital sciences
- Linköping University
- Nature Careers
- Swedish University of Agricultural Sciences
- University of Amsterdam (UvA)
- University of Basel
- University of Nottingham
- Wageningen University & Research
- Technical University of Denmark
- University of Copenhagen
- University of Sheffield
- Uppsala universitet
- Cranfield University
- Faculty of Science, Charles University
- Imperial College London
- KU LEUVEN
- LEM3
- Luleå tekniska universitet
- Medical University of Innsbruck
- Nantes Université
- SciLifeLab
- Slovak University of Agriculture in Nitra
- Tallinn University of Technology
- Technical University Of Denmark
- The University of Manchester
- Umeå University
- University of Antwerp
- University of Birmingham
- University of Cambridge
- VIB
- Vrije Universiteit Brussel (VUB)
- Wetsus - European centre of excellence for sustainable water technology
- cnrs
- Aalborg University
- BRGM
- CEA
- DIFFER
- ENVT INRAE
- ETH Zürich
- Ecole Centrale de Lyon
- European Magnetism Association EMA
- Faculdade de Medicina da Universidade do Porto
- Fundació per a la Universitat Oberta de Catalunya
- Hasselt University
- Helmholtz-Zentrum Umweltforschung
- IMDEA Networks Institute
- INRIA
- Institut National des Sciences Appliquées de Lyon
- Institute of Mathematics and Informatics
- Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S)
- Iquadrat Informatica SL
- Karolinska Institutet, doctoral positions
- Leibniz-Institute for Food Systems Biology at the Technical University of Munich
- Ludwig-Maximilians-Universität München •
- Lulea University of Technology
- Luleå university of technology
- Maastricht University (UM)
- Medizinische Universität Wien (Medical University of Vienna)
- Monash University
- NIOZ Royal Netherlands Institute for Sea Research
- NLR
- NOVA Information Management School (NOVA IMS)
- Reykjavik University
- Scuola IMT Alti Studi Lucca
- UCL
- UNIVERSIDAD EUROPEA
- Universite Gustave Eiffel
- Universite de Montpellier
- University College Cork
- University Medical Center Utrecht (UMC Utrecht)
- University of Bologna
- University of Bristol
- University of Chemistry and Technology, Prague
- University of Graz
- University of Southern Denmark
- University of Surrey
- University of Twente (UT)
- University of Warwick
- Université Gustave Eiffel
- Université Toulouse Capitole
- Université côte d'azur
- Université de Caen Normandie
- Université de Liège
- Utrecht University
- Vrije Universiteit Brussel
- Łukasiewicz PORT
- 84 more »
- « less
-
Field
-
model for the reactivity/selectivity in superacid conditions. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7285-FREGUE-005/Default.aspx Requirements Research FieldChemistryEducation
-
Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
geometric transformer model to predict protein binding interfaces in flexible and disordered regions. Cell Systems, 10.1016/j.cels.2025.101454 The PhD candidate will: Curate and analyze large-scale datasets
-
is to design a data architecture capable of harmonising sensor data and integrating them with artificial intelligence algorithms for predictive irrigation management. The research will include
-
that help determine when an AI model is ready for use and when more research is needed. PhD in Epidemiology on value-of-information from validating clinical prediction models and AI Our goal: Develop value
-
provide detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
-
that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model. The EngD project will: Investigate the multi-stage modelling
-
detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking
-
microstructural descriptors that are physically meaningful and predictive. Probabilistic surrogate modelling and digital twin construction. The extracted microstructural descriptors will be used to learn a
-
challenge is therefore to develop efficient surrogate models capable of rapidly predicting macroscopic mechanical properties directly from microstructural descriptors while preserving the underlying physical
-
sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the goal of enabling predictive, prescriptive, and pre‑emptive analytics. We work closely with