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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
with antennas, evaluate different algorithms for EM field strength data, investigating the minimal needed sensors (up to nine), and controlling the equipment using in-line measured data (closed-loop
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operating (Waterstromen) membrane-based wastewater treatment plants. As part of the UT team, you will develop a robust model predictive control (MPC) algorithm based on sensor and other system inputs that can
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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couplings—a key technology for achieving passive, high-precision, and deterministic alignment between precision components. Unlike active alignment methods that rely on actuators and sensors, kinematic
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total band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For more information regarding this position, you are welcome to contact Prof
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band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For additional information, please contact Prof. Dr. Erik Koffijberg
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with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in
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, allows for flexible sampling plans. Prof. Jelle Goeman co-developed the closed testing framework that gives flexibility for defining research questions in a data-dependent way. Thirdly, we add permutation