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performance in the required courses of the PhD programme will be evaluated by regular testing and confirmed by the supervisor. PhD students determine their individual courses of study in accordance with
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new routes toward energy efficient electronic devices with reduced heat dissipation, continued miniaturization beyond silicon based technology, and operation at much higher frequencies. The work will
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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, adaptability, and sustainability from the outset. By scientifically linking high-level performance objectives to system architecture and design decisions, this research aims to reduce costly late-stage redesign
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19 Mar 2026 Job Information Organisation/Company University of Innsbruck Department Faculty of Mathematics, Computer Science and Physics Research Field Physics Researcher Profile First Stage
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contribute to scalable, rational design strategies for next-generation porous carbon materials and high-performance energy storage devices. Research Objectives and Methodology The project will combine
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4 Apr 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 2 May
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English. Candidates may write their dissertation either in English or German. Programme duration 9 semesters or more Beginning Winter and summer semester Additional information on beginning, duration and
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the course requirements of the PhD program. The evaluation includes a review of the applicants’ previous academic performance and the quality of submitted writing samples and project plans. The evaluation
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
leverage machine learning techniques to bypass IO bottlenecks in the context of physics simulation on high-performance computing (HPC) clusters. This work is thus placed in a broader ``Machine Learning for