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: - A PhD degree in optimization or systems and control theory. - A strong mathematical background and an interest in conducting theoretical research. - A proven track record. - Excellent English
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Are you fascinated by application-oriented research in mathematics and eager to work at the interface of numerical optimization, optical design, and uncertainty quantification? In this PhD project
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optimization of these building blocks are essential for achieving breakthroughs in data rate, power efficiency, scalability, and overall system cost. This PhD project focuses on the electronic integrated circuit
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: Develop AI-assisted experimental workflows for oxide semiconductor deposition, aiming to accelerate process optimization and unravel new process–property relationships, and contributing to an EU Horizon
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twins, optimization, and control. In this PhD project, you will develop a new systems and control theory for learned operators, bridging modern scientific machine learning with classical control theory
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its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful
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to contribute to high-tech applications, state-of-the-art modelling or experimentation of advanced sustainable materials across the scales? We are looking for outstanding and enthusiastic PhD candidates, with a
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Employment 0.8 FTE Gross monthly salary € 4,925 - € 6,682 Required background PhD Organizational unit Faculty of Social Sciences Application deadline 13 October 2026 Apply now Are you passionate
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perform desktop studies related to process design and optimization, techno-economic evaluations, and screening of purification technologies. What are you going to do? The main objective of this EngD project
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critical for achieving power-efficient operation, programmability, high linearity and low-noise signal conditioning including optimal dynamic range and bandwidth utilization. This position offers a unique