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Field
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Analytics Software Engineering for Distributed Systems Telematics Theoretical Computer Science Optimal Transport Work on a scientific topic aims to enable the student to understand complex scientific work
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and optimize methods to measure neuronal activity and morphology.Combine the two methods to detect the cell type and neuronal physiology in one experiment. Computational & Data Analysis Apply advanced
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assess the operational feasibility and robustness of urban energy system designs emerging from AI- and multifractal-informed planning approaches. The PhD will develop and apply optimization-based energy
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investigate the optimal methods for combining multi-satellite InSAR with a network of Kurloo GNSS devices to provide robust 3D ground motion monitoring from space. The potential benefits may include
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Vacancies PhD position in Optimisation and Optimal Transport Key takeaways We are looking for a talented, research-oriented PhD candidate to join the NWO-VIDI project “SPARGO: Exploring and
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Analytical Food Chemistry at Technical University of Munich | Freising, Bayern | Germany | 5 days ago
Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jul 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within
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-temperature performance. The PhD project will focus on the development, investigations and optimizations of new electrode and electrolyte materials. The project will expand the student’s skill set in scientific research
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD candidate will be hosted at IRCELYON (UMR 5256
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on holistic understanding from regional net-zero. The PhD project is part of the Regional Energy, Carbon and Land Management initiative, focusing on optimizing energy infrastructure, land use and carbon flows
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through sensitivity, uncertainty, and scalability analyses. – Enhance the computational efficiency of large-scale optimization problems by exploring decomposition techniques, parallelization, and