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Field
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, Mathematics, Control theory, or any other related discipline, potentially with skills in Power Electronics Converters and Control. Applicants who are in the final phase of their master’s degree are also
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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PhD Fellowships in Physics at the Faculty of Science and Technology, Department of Mathematics and Physics. The start date is flexible, but must be no later than September 2026. This is a trainee
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inference and deployment costs (e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects
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awareness (SA), like our work on Situational Graphs (S-Graphs), improve on existing techniques by combining 3D environmental maps with detailed knowledge about objects into a single, optimized model. First
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advanced courses in Computer Science, Electrical Engineering, or Applied Mathematics. Alternatively, you have gained essentially corresponding knowledge in another way. The requirement for a degree must be
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logistics, energy systems, and AI-driven optimization. These problems are widely regarded as the natural domain of quantum computers, yet they remain extremely demanding for both classical digital computers
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theory, robust and optimal control, and physics-informed modelling, this research aims to bridge the gap between data-driven learning and dependable real-world autonomy. Aim You will have the opportunity
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microbiomes to optimize end-of-life material processing and circular resource recovery. This position will be part of the UT-ORII’s Circular Bioeconomy Systems (CBS) Convergent Research Initiative (CRI
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(PICs) increasingly used in various applications. To allow a smooth design flow for these PICs, optimized compact models are needed. This PhD position is enabling compact models for optical amplifiers and