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Field
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empirical perspectives. The NOMIS Fellowship Program supports groundbreaking research projects related to how images act as models or paradigms in scientific and aesthetic contexts. We are interested in
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and perform numerical simulations To be successful at Level B please address the selection criteria A PhD or equivalent in data science, social network analysis, mathematical modelling, statistics
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contextual scenarios. Develop a unified multimodal detection pipeline that integrates video, audio, and text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting zero-shot reasoning and
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of Biomedical Engineering and Imaging Sciences (https://www.kcl.ac.uk/bmeis ) is a cutting-edge research and teaching School dedicated to development, translation and clinical application within medical imaging
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Must be a U.S. Citizen Preferred Skills: Experience with MATLAB Familiarity with emerging technologies including instrumentation, computer modeling & simulation (e.g. Matlab, CFD, and/or other), and the
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of their development and structure. Working closely with colleagues at the Universities of Leeds and Reading, you will integrate theoretical understanding, observational data, and modelling approaches to improve
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be joining a multidisciplinary, international research team of physicists, climate modellers, oceanographers, and atmospheric scientists contributing to Antarctica InSync. You will play a central role
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: Star formation with a multiwavelength approach, covering from radio to high energy spectral range (contacts: Gemma Busquet, Núria Miret, Josep Maria Masqué) MHD simulation of star formation (contacts
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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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Investigate materials (electrode substrate, membrane and catalysts) Synthesis and interpretation of data Simple process simulation and modelling General lab organization and coordination Assist supervising PhD