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Field: Mining Engineering, Industrial Engineering, Data Science Duration: 12 months, renewable once. Location: UM6P, Benguerir Campus Preferred Start Date: As soon as possible Context and Objectives
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
Job Code: 09-25 Job Offer from July 04, 2025 The Max Planck Institute for Multidisciplinary Sciences is a leading international research institute of exceptional scientific breadth. With more than
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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should hold a PhD in biotechnology, biochemistry, chemical engineering, biomedicine or a related field. Experience in the following areas will be considered advantageous: Enzymology and carbohydrate
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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papers and presenting work at seminars and conferences. Required Knowledge, Skills, and Abilities: PhD in physical chemistry, or a related field. Preferred Knowledge, Skills, and Abilities: Experience in
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robots are therefore required. One of the goals of this project is to commercialise. You must have a strong computer science background and have experience in one or more of the following areas: Computer
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+ imaging, data analysis and neuronal circuits. Requirement PhD in neuroscience, computer science or a related field High motivation for explorative research Experience in neurophysiology (electrophysiology
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The Faculty of Engineering, Department Elektronica en informatica, research group Electronics and Informatics: Research – Development - Innovation, is looking for a postdoctoral researcher. More
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data