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-quality papers in top journals and conferences. The appointees will be required to: (a) develop novel AI and XR algorithms/software for medical image analysis and computer-assisted surgery tasks; (b
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-modal fusion techniques for localization and mapping; (b) develop and implement algorithms for autonomous robots; (c) design and execute experiments to validate and refine algorithms and systems; (d
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"Practical Quantum Advantage of Reservoir Computing on NISQ Devices." Position Overview The successful candidate will conduct research in quantum and quantum-classical algorithm development, focusing
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- “Data-driven algorithms for multi-product inventory systems with non-stationary demand”. Qualifications Applicants should have:- (a) a doctoral degree, preferably in the area of operations management
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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noise, allowing only specific algorithms with relatively shallow quantum circuits to be executed. In the NISQ era, hybrid algorithms run partially on quantum computers and partially on classical computers
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in algorithms development and refinement; (b) a good command of both written and spoken English; and (c) at least two first-authored publications. Preference will be given to those with: (a
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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) and common data formats (e.g. RVT and DWG). Preference will be given to those with experience in computer graphics, 3D geometric algorithms or WebGL development. Applicants are invited to contact Prof