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-of-the-art semantic and instance segmentation algorithms for 3D and 4D microtomography data. The project has a particular focus towards analysing fibre-based materials but will also consider other material
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. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). A broad understanding of machine learning methodologies and
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks
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control, machine learning, and differential geometry to work on the development of advanced algorithms to enhance the safety and robustness of human-robot interaction. The successful applicant will engage
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twins together with two PhD students, especially to propose new models and algorithms for complex maneuvers, and building a parametric autonomous model of drivers reproducing a close to reality human
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of stroke patients and healthy volunteers. Developing algorithms for identifying and excluding motor unit filters associated to impaired motor units. Integrating real-time-decoded features of motor unit
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project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance algorithmic justice through participatory design” (PARTIALJUSTICE) to examine issues of justice and participation in
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significant progress toward the understanding of these blinding diseases and their research has been published in translational journals. The PI has received multiple NIH grants to study these ocular disorders
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past