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21 Feb 2026 Job Information Organisation/Company CNRS Department Institut des géosciences de l'environnement Research Field Environmental science Environmental science » Earth science Environmental
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. The Materials for eXtremes (M4X) research group (https://more.bham.ac.uk/M4X/ ) investigates new alloys for extreme environments from fusion & fission reactors, to aerospace gas turbines and concentrated solar
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, “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
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approximately 25 doctoral scholarships and some postdoc positions. More information can be found here: https://www.ntnu.edu/mai The appointment is carried out in accordance with the principles of the State
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performance degradations and unwarranted system failures can occur. There is certain physical information known a priori in such aerospace platform operations. The main research hypothesis to be tested in
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, funded by the European Commission. You can find more information on this project at NEWTON, https://newton-6g.eu/ . The Doctoral Network is led by IQUADRAT, the ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS
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- See advert for details Deadline: 13 April 2026 Supervisors: Dr Subhash Lakshminarayana (Lead) and Dr Michael Faulkner Safeguarding Power Grid Stability in the Age of Artificial Intelligence (AI) Data
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UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments
10th April 2026 Languages English English English UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments Apply for this job See advertisement About the
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the future? PhD Candidate in Data-Driven Methods and Sustainable Materials for Offshore Wind Apply for this job See advertisement Welcome to USN The University of Southeastern Norway (USN) ranks as the
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore