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: Experience in protein or biologics formulation Knowledge of SAXS, light scattering, or other solution-state biophysical characterization methods Familiarity with AI-driven modeling tools (e.g., AlphaFold
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of Leeds (https://www.leeds.ac.uk/international-students ) Desired skills: Some knowledge of Physical and Analytical Chemistry (experimental chemistry to investigate heterogeneous processes particle surfaces
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Language Processing, can be used to extract linguistic knowledge, particularly concerning tones. The main object of investigation will be the Yongning Na language (ISO code: NRU). This work, based on fine-tuning models
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Infrastructure? No Offer Description The Centre for Lithospheric Research (https://clr.geology.cz/ ) was established in 2012 within the Czech Geological Survey on the basis of an initiative by the Czech government
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quality and climate. Our goal is to understand how these gases are produced and removed in peatlands and to bring this knowledge into climate models. Project links - https://villumfonden.dk/en/projekt
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Department: Geological and Mining Engineering. Knowledge area: Mining. Teaching
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
. Candidates must possess an exceptional background demonstrating expertise across atmospheric physics, computational modeling, and data science. Knowledge of atmospheric science or meteorology, and computer
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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Sharing – Building a federated data space to enable responsible data integration and cross-project learning. AI & Modelling – Using shared data to power advanced models that help describe and predict