137 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Leibniz in Germany
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adjustments are required. The ultimate goal of this master’s thesis is to find a more robust solution based on machine learning (ML). Reference number 10/26 Your tasks Analyze white-light reflectance (WLR
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) Focus on Microbiome Data Science and Explainable Machine Learning Core research themes We are looking for motivated and skilled students to join our research team in the field of plant microbiome data
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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mechanisms of learning, memory formation, perception, and behavior. Researchers with a proven track record in neuroengineering and related fields — including neuro-inspired hardware, brain-machine interfaces
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accessibility by public transport or car (including free parking) 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The BIO-MICRO project Please find a description of
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. The positions focus on applied machine learning methods for real-world systems. Possible research directions include: Transfer learning and domain adaptation across heterogeneous production environments (e.g
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, starting 01.06.2026, ending 31.05.2030): Postdoc position (f/m/d) in the department “Competencies, Personality, Learning Environments” (Focus: socio-emotional and cognitive competencies) The Leibniz
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of nutrition and health, with the aim of understanding the molecular basis of nutrition-dependent diseases, and of developing new strategies for treatment and prevention (https://www.dife.de/en/). We invite
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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in