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collaborative and international projects Experience/knowledge in HIL systems Hands-on lab experience and/or interest Knowledge on Machine Learning, or other AI techniques Team Worker Initiative in Research and
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. The interests of LABS are to develop and apply statistical, machine learning, and artificial intelligence (AI/ML) methodologies to "big data" in multi-omics and medical data for aging and diseases, such as
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project “Analytics for Learning with Machines” (ALMA) The position is TV-L E13, 75%, limited to 3 years, funded by the Deutsche Forschungsgemeinschaft (DFG). The project is a Franco-German collaboration
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for renewal for an additional term based on institutional needs. Visiting Lecturers carry a 5-5 teaching load. We seek to hire a candidate with strong teaching credentials to teach our introductory course in
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how
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demonstrated experience of writing technical reports. *Candidates must demonstrate an awareness of equality, diversity and inclusion agenda. Desirable: *PhD in machine learning, artificial intelligence, data
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, statistics and probabilities • data science, machine learning, artificial intelligence • optimisation • power system management, integration of renewables • energy forecasting Expected level in french : bon
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Back to Overview Research Assistant / PhD Student (m/f/d), Machine learning chiral molecules, 75%Full PhD Working LanguageGerman, English LocationKassel Application Deadline20 Feb 2026 Starting
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Location Lexington, KY Grade Level 12 Salary Range $62,400-111,634/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https