25 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at Leibniz in Germany
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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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, 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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further both professionally and personally in an interdisciplinary setting. Position DWI is looking to fill the position as soon as possible: Research Scientist Machine Learning Engineer - AI-Powered Image
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based on machine learning. Reference number 08/26 Your tasks 1. Assessment and analysis of GaN technology characterization data Identification of outliers during testing, with and without machine learning
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, informatics, physics or a related field strong expertise in machine learning strong interest in high performance computing on CPUs and GPUs proficiency in Fortran, Python, shell scripting proficiency with Linux
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based on machine learning. Reference number 05/25 Your tasks Assessment of GaN technology in possible novel integrated GaN RF front-end configurations - Full duplex in-band transceivers - Integrated down
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machine learning algorithms Strong communication skills and ability to work in interdisciplinary teams Fluency in spoken and written English We offer: A dynamic and interactive research environment as
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information retrieval, data integration, machine learning/AI, LLMs, knowledge graphs excited to use vector databases, e.g. integrating deepset haystack for RAG interested in experimenting with solr, postgres
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), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack