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to interact and collaborate to develop robust ways to decode single molecule imaging data. Your profile The candidate should hold a PhD in biophysics, chemistry, nanoscience or related subjects and have a
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analysis, manuscript preparation, and project reporting Required Qualifications PhD (or equivalent) in nanotechnology, biomedical sciences, cancer biology, or a related field Proven experience in
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and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
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combining CRISPR-based endogenous protein tagging, advanced quantitative imaging, and biochemical approaches, this project seeks to uncover novel principles of replisome plasticity. A key long-term objective
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to prototype validation and measurement activities. Document design choices, trade-offs, and experimental results in high-quality publications. The position offers the opportunity to establish an independent
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hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project