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Team up with up to 3 fellow Ph.D. students in the DSP-assisted Wideband & Efficient Transceivers (SWEET) project which is part of the WiTECH center to perform cutting-edge multi-disciplinary research in system and circuit design for next generation wideband radio frontends. The position allows...
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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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. will be developing efficient and reliable algorithms that arise in the context of topological data analysis and rendering for the visualization of large amounts of data. Close cooperation with other
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, optimization) or AI.- Someone who enjoys working in a team, takes initiative, and isn’t afraid to think outside the box.- Someone with excellent grades from BSc and MSc studies, and not afraid of experimental
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of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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part of the MARTINA project and will explore the application of co-design optimized machine learning and neuromorphic solutions for applications that are challenging to address using conventional
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application no later than August 1, 2025. Project description Linear algebra expressions are evaluated in an efficient and robust way by mapping them to a carefully chosen sequence of calls to optimized