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09.12.2025 The Hector Research Institute of Education Sciences and Psychology at the University of Tübingen invites applications for the following position: PhD Position on Computational Modelling
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computational optimization of additively manufactured Mg alloys for biodegradable implant applications. Host: Helmholtz-Zentrum Hereon, Geesthacht, Germany, with PhD degree awarded by Kiel
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research school on secure distributed computing (SeDiC) is proposed. SeDiC aims to tackle the challenges of exchanging and computing data across a network of interconnected systems. It addresses scalability
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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related field strong background in distributed systems, real-time computing, or networked control systems knowledge of UAV systems, swarm coordination, or digital twin frameworks experience with programming
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products. By systematically examining how water and ionic environments influence reaction pathways, we aim to uncover fundamental principles that govern product distribution and catalytic performance. Close
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promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried
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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 We are announcing a 65% PhD position (m
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 16 hours ago
(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction