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Field
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is expected that the postdoc in this position will seek funding (e.g., an NIH NRSA award) for continuing the position after the first year. Applicants must have completed the PhD by the date
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of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop software prototypes for AI-for-Science systems tailored to scientific discovery and data
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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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transformations. Combining automated reaction discovery simulations, microkinetic modelling, machine learning, and global optimization, this project will develop a new and exciting route to addressing one
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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a wider ERA Chair team in interdisciplinary aspects such as microfluidic design and machine learning, however it is anticipated upon completion of the PhD the candidate will be positioned as a world
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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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scientific journals Requirements: completed scientific university degree and, if applicable, PhD: either in computer science, data science, bioinformatics, or a related field with a focus on machine learning
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hands-on experience in areas such as computer vision, deep learning, multi-modal sensing, robotics, structural health monitoring, or digital twin technologies. (Fresh PhD graduates are welcome
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construction, and phylogenetic placement Ability to assess where machine-learning approaches may complement existing bioinformatic and phylogenomic methods, particularly for improving taxonomic resolution Skills