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industrial engineering of similar Interest in the practical testing of catalysts in laboratory-scale pilot plants Enjoyment of exploratory work with great scientific potential Ability to analyse complex
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pollution, support biodiversity and deliver social value. Yet these trade-offs remain poorly quantified in complex urban landscapes. This PhD will investigate how urban blue networks can be optimised for both
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polynomial order is considerably more complex, especially around intricate aerodynamic surfaces. Instead of replacing current industrial meshing practices, the project proposes a hybrid strategy: low-order
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complexity seen in patients. This Marie Skłodowska-Curie Actions (MSCA) doctoral network PhD project takes a fundamentally new approach: embedding animal models in a translational framework that connects
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 20 days ago
the PhD by G. Sporschill, plus some confidential Airbus configurations; high-lift configurations both clean, and including complex ice accretion shapes. The curved mesh technological bricks will be
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simulation of technical systems Interest in practical work with catalysts, laboratory setups and pilot-scale plants Ability to analyse complex interrelationships and work methodically Good written and spoken
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Decision Making (DC7) at Adhera Health SL (Spain) and the University of Bergen, Norway. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148
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frequency regulation, energy scheduling, and overall smart grid system optimization. Moreover, such complex interconnections between power system dynamics, communication networks, and information
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the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway. Supervisors: Dr. Luis Fernandez-Luque, Dr. Ana Moro (Adhera Health SL); Prof. Helge Ræder, Prof
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their applications. Using machine learning and related tools to enhance quantum memory advantages in stochastic simulation. Using advanced tensor network techniques to enhance the modelling of complex, memoryful open