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Field
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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Education: PhD in Artificial Intelligence, Bioinformatics, Computer Science, Physics, Engineering, or a related field. Programming: Proficient in Python. Machine Learning: Strong experience with frameworks
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or artificial intelligence; • A good team spirit and willingness to collaborate; • Very good command of the English language. These skills would be an advantage: • Experience with Lagrangian transport
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and risks (CREER), artificial intelligence and industrial and digital engineering (CERIS). It has 12 technology platforms and 1,600 partner companies. The position is part of the European BEST-CROP
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning
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/artificial intelligence; (f) health policy, health economics, and decision science; (g) and implementation science Eligibility The ideal candidate will have an MD/DO, PhD, or ScD. PhDs/ScDs may be in clinical
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(MaaS), electric vehicles, artificial intelligence in travel behavior modeling and multimodal transportation network analysis. The person will also interact with, mentor, and assist graduate and
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research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/ Qualifications To be appointed under
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awareness. We welcome applications from recent PhD graduates in relevant areas, such as artificial intelligence and natural language processing. An ideal candidate will have a strong technical background in
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QGG Aarhus University seeks two Postdoctoral researchers in Quantitative Genetics of sustainable ...
more than 20 countries. We perform basic and applied research within plant, livestock and human quantitative genetics. Our focus areas include quantitative genetics, artificial intelligence applied