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Field
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Experience: In the development of medical devices in vision sciences. Implementation of psychophysical algorithms for vision. Design and analysis of clinical studies. Experience in functions similar to those
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programming, session types, etc.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops, software engineering (software product lines), human factors in security and privacy, post-quantum
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researchers and faculty of EEWRC to fully utilise the field of energy management and Distributed Energy Systems to propose, drive and implement relevant research lines. This role is designed for someone eager
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internal equity. Pay Range: 77,000-80,000 A postdoctoral scholar is sought for a position in SEA-Scan: Structural and Environmental Algorithms for Sensing of Offshore Systems working with Dr. Barbara
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distributed quantum computing. The center includes other quantum faculty, and conducts a wide range of collaborative quantum research in the areas of quantum computing, quantum algorithms and complexity
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implement algorithms, models, and software applications that can be translated to clinical use. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be
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/356343/postdoc-position-modelling-impa… Requirements Specific Requirements You hold a PhD degree in ecology or environmental science. You have proven experience with quantitative analytical methods (meta
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: Professor Zhongwen Zhan) to design, build, and validate a miniaturized Distributed Acoustic Sensing (DAS) system for the lunar environment. Key responsibilities: - Architect and prototype a low-SWaP (Size
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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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implementing algorithms based on online Sparse Gaussian Processes and advanced probabilistic techniques enabling AUVs to dynamically alter their trajectories, cutting down on uncertainty and improving efficiency