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- UiT The Arctic University of Norway
- University of Plymouth
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- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
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- Max Planck Institute for Biogeochemistry •
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relevant programming languages, particularly python Knowledge of, and experience from, the maritime industry Knowledge of generative models, reinforcement learning, or geometric deep learning. Experience
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skills in relevant programming languages, particularly python Knowledge of, and experience from, the maritime industry Knowledge of generative models, reinforcement learning, or geometric deep learning
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the SDM modelling for these five gorgonian species to deeper area in the NW Mediterranean sea. - run BIOMOD2 suite on Blouet et al. (2024) dataset - gather environmental descriptors for extending the SDM
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the following fields: Large Language Model-based application development. Knowledge Graph Development for Sensor Data. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial
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exchanged between land, ocean and atmosphere through processes known as global biogeochemical cycles. Research activities in the IMPRS-gBGC aim at a fundamental understanding of these cycles, how