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Per Week 38,7 Offer Starting Date 1 May 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number 101227683 Is the Job related to staff
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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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endorsed Curtin SHAPE activities Please note: The Scholarship for High Achievement and Performance Engagement (SHAPE) currently recognises the following programs: AHEAD Yr7 Program AHEAD Yr8 Program AHEAD
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MSc program - art. 6º, n.4 b) https://diariodarepublica.pt/dr/detalhe/regulamento/950-2019-127238533 https://files.dre.pt/2s/2019/12/241000000/0009100105.pdf subject to suitable performance within
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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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their own research project (under supervision). The programme culminates in the submission of a PhD thesis, which the student must defend in public. The programme is prescribed to 180 ECTS credits
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2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Almost one
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populations Supporting the implementation of computation frameworks to predict the metabolic activity of cell populations from omics data Performing phenotypic assays to validate the cellular heterogeneity
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 22 days 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