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Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
twinning for production and process optimization. A first-of-its-kind pilot factory is now based at Aarhus University (AU Viborg), and has been equipped with about 200 sensors and a production management
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spatial variability of soil health. You will be contributing to specifically the area of using proximal and remote sensors, soil physical, chemical and biological data, as well as plant and weather data
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discipline (e.g. Medical Informatics, Computer Science, Data Science, Computational Social Science, Epidemiology, Biostatistics, etc.) Strong research track record, programming, and implementation skills
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world-class clinical and computational teams, with full intellectual ownership. Publish influential research, supervise students, and contribute to grant applications as a named investigator. Leave with
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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, and computation in a collaborative environment, offering postdocs the chance to lead high-impact, interdisciplinary projects at the forefront of neuroengineering. We are recruiting a highly motivated
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. We embrace diversity, promote potential and are committed to educational justice worthy of the name. The University of Duisburg-Essen (UDE) at the Duisburg Campus, in the Faculty of Physics, is looking
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international conferences. Your profile Applicants should hold a PhD in physical chemistry, material science or similar related subjects and have experience and expertise in small-angle X-ray scattering(SAXS
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, that align with and advance current research initiatives. Applies for independent research funding; mentorship and support will be provided to facilitate this process. Performs other duties as assigned
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; Couple the model to a 1D physical model (GOTM) through the FABM framework; Validate the coupled model using published and newly gathered observational data; Conduct numerical experiments to understand