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is looking for a PhD Student (f/m/d) - Electrochemical swing adsorption of carbon dioxide. Your tasks Performing quantum mechanical and ML-based simulations to determine CO2 adsorption energies
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powerful high-throughput platform to generate the high-quality experimental data needed for advanced thermodynamic modeling. This PhD project aims to bridge the gap between experimental data high throughput
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, - openness to collaboration with industrial partners (Airbus) and have a strong interest in aerospace modelling projects. The candidate must hold a PhD in mechanical engineering, aerospace engineering or a
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Leipzig, Sachsen | Germany | about 15 hours ago
EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Part-Time Suitability: The position is suitable for part-time
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 15 hours ago
a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Part-Time Suitability: The position is suitable for part-time
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science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 6 Apr 2026 - 23:59 (Europe/Amsterdam) Country Switzerland Type of Contract Temporary Job Status Full-time
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their seniority, roles and preferential behaviour. The aim of the PhD is first to characterize the mechanisms that may be needed to model the dynamics a Wikipedia project, and define several levels of modelling
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD student will work in the SICAL team at LIRIS, recognised for its
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be tasked with investigating the molecular mechanisms of endoplasmic reticulum-mediated protein quality control using Arabidopsis thaliana as a convenient genetic model system. Requirements
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team as a PhD candidate to work on beyond the state-of-the-art model distillation and robustness methods, enabling efficient, reliable inference for challenging real-world problems in the semiconductor