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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process
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sustainability, performance, and reliability. Our research leverages optimization techniques, applied machine learning, and statistical analysis to achieve these objectives. Through the DecAI project we will work
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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at Université Paris-Saclay (https://cvn.centralesupelec.fr/ ), Prof. Pock from the Institute of Computer Graphics and Vision at Graz University of Technology (ICG ), Prof. Thiran from the EPFL Signal Processing