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ice, using a framework consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ
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measurements and/or Computational Fluid Dynamics (CFD) simulations. Specifically, you will assess where simplified assumptions in the model fall short. You will then train a machine learning model (such as PySR
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Research Infrastructure? No Offer Description Do you want to develop a foundation model for one of biology’s most complex ecosystems? By joining the European Innovation Council (EIC) Pathfinder project NOAH
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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
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into solid phases of marine snow. You will test the performance of your model by simulating experimental and field data in collaboration with the PHOSFLUX PhD student. Your qualities We are looking for a
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consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ and remote sensing data from
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which factors determine feasibility and performance. What will you do? Improve, document and apply a regional groundwater model for variable-density flow groundwaterflow and coupled salinity simulations
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Do you think that quantum computing can open genuinely new routes for analysing biological data? Are you excited to work where bioinformatics, molecular modelling and quantum algorithms meet? Join
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collide, condense and evaporate. Guided by the results from the field campaigns, a new Microphysics Informed Large-Eddy-Simulation (MiLES) model will be developed. The tested and verified MiLES will be
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planetary atmospheres. The Section also initiates and manages a wide range of related modelling, software and hardware R&D activities. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s