Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Aalborg University
- Linköping University
- Umeå University
- BRGM
- CNRS
- DAAD
- Empa
- Forschungszentrum Jülich
- Helmholtz-Zentrum Hereon
- INRIA
- Imperial College London
- Inria, the French national research institute for the digital sciences
- Leibniz
- Loughborough University;
- Nature Careers
- Technical University of Denmark
- Umeå universitet
- University of Basel
- University of Exeter;
- University of Lund
- University of Plymouth
- 11 more »
- « less
-
Field
-
, “Generative diffusion models for atmospheric data assimilation” (f/m/d) The position is offered for three years with a start date as soon as possible. The salary is according to class EG 13 TV-L. The fixed-term
-
Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
-
well as LiDAR measurements, into ensemble agroecosystem model simulations. The successful candidate will play a key role in developing robust landscape-scale digital twins and advancing data assimilation
-
to the development of a comprehensive and robust model (data assimilation) of the Rhine Graben. The approach will be a hybrid data assimilation, physical model coupled with a neural network (PINNs). The use of soft
-
modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
-
boundary treatments. Integrating the surrogate models into a digital‑twin pipeline for real‑time data ingestion, assimilation, and visualisation. The project will deliver a real‑time digital‑twin
-
of inversion or data-assimilation approaches that exploit the totality of data from both measurement and modelling. Third, the project will quantify uncertainty arising from flow variability, measurement noise
-
education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Molecular Biology/Umeå university, are searching for a DDLS PhD student in Data driven
-
computational engineering and computer simulation data modeling and assimilation towards experimental measurements under consideration of uncertainties utilization of Explainable AI techniques to enable novel