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Denmark, invites candidates for a fully funded PhD-position starting 1 March 2026 or as soon as possible thereafter. The position is for 3 years. The position and the project The chosen candidate will join
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related disciplines Quantitative imaging, data analysis, or computer vision Numerical modeling of biological systems or continuum mechanics Machine learning/AI, particularly explainable AI (XAI) Hands
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for a/an PhD candidate (Life Sciences) 50 Faculty of Life Sciences Startdate: 2025-11-01T00:00:00Z | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until
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) to predict, observe, and manipulate epigenetic processes. The Schneider group is looking for a PhD candidate (f/m/x) to work on the interphase between epigenetics and cellular metabolism. The applicant should
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 23 minutes ago
Job Offer from October 20, 2025 The International Max Planck Research School for Ultrafast Imaging and Structural Dynamics in Hamburg, Germany, offers a structured PhD program focusing on ultra-fast
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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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to the interior of the cell. GPCRs are involved in multiple physiological process including cell growth, neurotransmission, metabolism & immune response; they can misfunction in disease and consequently have served
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into the generation process. This multidisciplinary project will deliver deployable models, reproducible methods, and, where allowed, shareable datasets. The student will gain training in deep learning, AI, image
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in Lithium-Ion batteries, image analysis, multiphysics modeling, artificial intelligence and your motivation to pursue a PhD CV Bachelor’s and Master’s Transcripts List of 3 references Please note that
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frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data