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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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of the ECHO-EMG research initiative, funded by the Independent Research Fund Denmark (DFF). The project aims to develop a novel system that combines high-density surface electromyography (HD-sEMG) and
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learning (ML) for high-fidelity data ‘stitching’. The integration of data from multiple analytical platforms is critical for advancing the understanding of complex biological and chemical systems. This work
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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Mesoscale Convective Systems (MCSs); organized systems of deep convective cells that can span 100 kilometres and persist over multiple hours. In tropical South America, 40-60 % of the rainfall can be related
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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Description The Chair of Transport Modelling and Simulation at TUD Dresden University of Technology is investigating models, algorithms and simulations to achieve an enhanced scientific
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Your Job: Random unitaries are a ubiquitous tool in quantum information and quantum computing, with applications in the characterization of quantum hardware, quantum algorithms, quantum cryptography
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motors and braking technology, high-torque density axial flux electrical motors, development of servo controllers and algorithms, and special electrical machines such as superconducting electrical motors
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the Novo Nordisk Foundation, that will drive research and innovations at multiple levels - from developing scalable quantum processor technologies to solutions for the quantum-classical control and readout