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20 Feb 2026 Job Information Organisation/Company NORCE Norwegian Research Centre Department Energy Research Field Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1
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conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
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chemical biology and biotechnology, enabling the preparation of defined oligonucleotides for a wide range of research applications. This project focuses on the experimental development and optimization
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 2 months ago
implementation of advanced algorithms, including variational and optimization-based approaches # Investigation and adaptation of mathematical methods in hybrid classical–quantum computing contexts # Documentation
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computer science, mathematics, data science, or any computational science discipline who have received their Ph.D. and have completed no more than three years of postdoctoral work are encouraged to apply. Only one
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facilities, and opportunities for professional development (https://www.helsinki.fi/en/about-us/careers ). YOUR PROFILE PhD in biology, mathematics, or a related field Strong background in mathematical
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mathematics Application deadline: February 23, 2026 Doctoral student in Geometric Hydrodynamics Application deadline: February 23, 2026 Doctoral student in discrete optimization and computational complexity
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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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Description The PhD researcher will work on the Inventory-Routing Problem with Pickups and Deliveries (IRP-PD) under demand and supply uncertainty. The IRP-PD requires the joint optimization of inventory and
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algorithm and infrastructure integration, with responsibilities spanning optimization tuning, heuristic development (e.g., Tabu Search), performance diagnostics, and production-level feature development