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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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AI models for network operations. This project is a joint effort between the University of Twente and TU Delft. You will be co-supervised by Associate Prof. Pedro P. Vergara from TU Delft and
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application For more information about the position, you can contact Dr Caroline Gevaert (email: c.m.gevaert@utwente.nl) or Prof Raúl Zurita-Milla (email: r.zurita-milla@utwente.nl). You are also invited
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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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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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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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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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, 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
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: CV (including contact information for at least two academic references) Title and abstract of your Master’s project/thesis. For more information on this position, please contact Prof. Sarthak Misra