49 ensemble-prediction positions

Research Fellow HEPPI

convolutional ANNs, for postprocessing ensemble precipitation forecasts over India from the National Centre for Medium Range Weather Forecasting (NCMRWF) global ensemble prediction system (NEPS-G). Develop

4-year Postdoc position on AI and S2S prediction

the project ASPIRE - Advancing Subseasonal Predlctions at Reduced Computational Effort, which is funded by the European Research Council (ERC) through a Starting Grant. AI-based weather prediction models

EngD on Software development for advanced synthetic microstructure generation

modular, have a graphical as well as a scripting interface and should be extendable, so that it may serve as a platform for further development. As a validation, ensembles of synthetic microstructures

PostDoc Researcher - EdgeAI-Trust Project (R2)

-based in-vehicle distributed predictive maintenance system. 3. Devise appropriate AI architectures leveraging AI features such as explainability, interpretability, traceability, and leveraging AI

Research Fellow (Computational Biologist)

proficiency in developing ML/AI-driven biodesign models, particularly in the context of understanding and predicting microbial cellular mechanisms and cell design principles. The successful candidate will

Theory of the complex luminescence properties of actinides

of electronic correlation and relativistic effects, and this on an ensemble of quantum states of different nature. However, there is a major challenge in understanding these properties and more broadly all the

Meteorology Research Assistant-Didlake

conduct collaborative research supervised by Associate Professor Anthony Didlake and Assistant Professor Xingchao Chen. The research project will investigate the physical processes and predictability

EngD on Software development for advanced synthetic microstructure generation

should be extendable, so that it may serve as a platform for further development. As a validation, ensembles of synthetic microstructures mimicking real materials will be generated, which will then be

Post-doctoral research position Predicting Environmental Changes Using Deep Learning, Satellite Remote Sensing and Future Climate Projections. Case studies in Southern Kenya and the Brazilian Amazon

to constructing sophisticated models designed for the prediction of pivotal future events that may impact these areas. Such efforts aim to facilitate the adoption of anticipatory mitigation tactics. For example

Postdoctoral and research engineer positions on data assimilation for the atmospheric composition (R2)

currently composed of about 30 people among researchers, engineers and students of different nationalities. It aims at better understanding and predicting the spatiotemporal variations of atmospheric