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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 11 days ago
biology, in particular on single-cell genomics. We are looking for a highly motivated PhD Candidate (f/m/x) in Machine Learning (ML) or Computational Biology to join a collaborative research project with
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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established competence networks. Duties As a PhD student, you will perform both experimental and theoretical work. You will learn how to collect and analyze scientific data within your research area as
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hydro-climatic conditions govern vegetation behaviour, and how vegetation impairs the functioning of drainage and water-management assets. Using advanced geospatial modelling, machine learning and digital
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. The selected candidate is expected to teach courses on topics in the field of quantitative finance, machine learning and data science. Courses should be offered in Polish and/or English Academic organizational
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combinations of structural and functional properties, using both simulations for machine learning and experimental validation. Fabrication tools and methods are already established in our laboratory. Key
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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projects and deliverables May supervise undergraduate students working on the AI/ML projects QUALIFICATIONS PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations