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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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biomedicine and digital pathology Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability
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PhD Student (gn*) Job Id: 11029 Limited to 3 years | Part-Time with 65% | Salary according to TV-L E13 | Institute of Molecular Tumor Biology We are UKM. We have a clear social mission and, with
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University of Vienna, the PhD program for life scientists and computational scientists/machine learning experts will start in January 2026. The goal of the PhD Program is to address real-world problems in
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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information about the role, please contact Prof. Radu State Your profile Strong background in AI, machine learning, or multi-agent systems, ideally with interest in financial systems, decentralized ledgers
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin