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Field
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MODELLING Offer of job position: We offer a R1 position for 2 months in the framework of the Industrial PhD programme titled “Local Energy Communities Optimal Management and Integration” Salaries will be paid
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PhD in organic chemistry (M/F) – Development of self-optimizing flow reactors for chemical reactions
degree or a degree from an engineering school, preferably in cheminformatics, chemical engineering, or organic synthesis. Knowledge of computer programming and/or optimization is strongly preferred
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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 The Concrete
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Challenge: Extreme water events threaten people and infrastructure Change: Understand impact dynamics with experiments and numerical simulations Impact: Optimize the design of resilient
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and prior knowledge of the sample geometry. You investigate and optimize the trade-off between accuracy and imaging speed. For real-time application, the speed and accuracy of the algorithms will be
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 28 days ago
21 Aug 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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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 Aalborg University, Department of Energy, Campus Esbjerg, invites
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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 We offer a PhD
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real‑time anonymization in practice. The researcher will develop hardware‑aware neural architectures with hardware-in-the-loop optimization and efficient inference strategies to meet the computational
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to increase resource use efficiency. However, managing and optimizing these new cultivation systems requires crop models that can predict plant growth, crop yield and resource use under highly dynamic