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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in
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collection algorithm participate in data collection and dataset creation assist in quantitative data analysis collaborate on writing academic articles and research reports Where to apply Website https
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position in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers
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learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows for crafting
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deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows
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secondments. The project envisages the following secondments: a three-months secondment to learn novel algorithms form improving fecal MP samples' taxonomic and functional characterization (Prof. Bart Mesuere
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processing, inverse problems and data science with emphasis on analysis, optimization, numerics and algorithmic solution Collaboration in interdisciplinary cooperation projects and third-party funded projects
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an experimental cryo-EM laboratory (Prof. Danny Hsu’s group, Academia Sinica, Taiwan), the postdoc will: i. develop and test fitting algorithms on fully synthetic cryo-EM maps generated from simulations, ii
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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise-Aware Optimizations for QML, QML Security, Error Correction for Quantum Computing, Secure Quantum-Classical