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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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for downstream analyses. Data & documentation Analyze flow cytometry and functional assay data. Document experiments and prepare figures and summaries Collaboration & development Work in an interdisciplinary team
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with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) A high motivation and the ability to work independently with a strong team orientation Excellent spoken and
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mutations. Working closely with the PI (Professor Peter Visscher), you will develop new research methodologies, conduct analyses on detailed and complex data, write articles for peer-reviewed journals and
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical engineering, computer science & IT
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subtype of dementia. Your tasks This interdisciplinary PhD project combines atomic force microscopy, fluorescence microscopy, chemical spectroscopy, biophysics and data analytics. The PhD student will be
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AI4TECS aims to develop the first AI‑powerAd system that integrates real‑time EC identification using non-target high resolution mass spectrometry data, toxicity prediction, and transformation modelling
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of the developed drug delivery system. The results of this project may lead to the identification of a novel drug delivery system to treat sarcoma using photodynamic therapy. Further information: This three-year