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company METzero Technologies . Research Objectives 1. Process Intensification & Scale-Up Design and evaluate scalable MEC configurations Apply computational fluid dynamics and transport modelling to resolve
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
Researcher (R1) Application Deadline 30 Sep 2026 - 15:14 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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quantum computing. We explore new ways to build sensors, such as continuous optical clocks, and collaborate with industry, startups and users to bring quantum technology to the market . This project is
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3 Aug 2026 Job Information Organisation/Company Politehnica University of Timisoara Department Department of Automation and Applied Informatics Research Field Computer science » Systems design
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of Electrical Engineering, Mathematics and Computer Science (EEMCS), an internationally recognized research group in wireless communications, embedded systems, and distributed intelligence. Depending on your
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of the nuclear interaction, which governs neutron skins, the nuclear symmetry energy, and the equation of state of neutron-rich matter. The resulting posterior distributions will be propagated to neutron-star
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Programme? Not funded by a EU programme Reference Number 256/DRB/045 Is the Job related to staff position within a Research Infrastructure? No Offer Description Your function As a PhD student, you will
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eating disorder researchers and clinicians, (d) distribute scientifically-based prevention programs across the community, (e) advocate for more awareness, better treatment, and services for eating
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thesis in the field of continual graph learning. Continual graph learning studies how graph neural networks can learn from a sequence of evolving tasks, graphs, or distributions while retaining previously