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, you will contribute to impactful research in optimization. About us The department of Mathematical Sciences has about 200 employees and is the largest department of mathematics in Sweden
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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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mindset and intellectual curiosity to strengthen and complement the research profile of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund
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residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme. Applicants who
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of the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University. The research group, which is headed by Jakob Nordström , is also active
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Description of the workplace The PhD student will be working in the Mathematical Insights into Algorithms for Optimization (MIAO) group at the Department of Computer Science at Lund University
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BBSRC Yorkshire Bioscience DLA Programme: Harnessing JAK-STAT signalling for optimal innate immune cell function School of Medicine and Population Health PhD Research Project Competition Funded
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications. Host: Helmholtz-Zentrum Hereon
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) position in Materials Engineering with focus on computational optimization of additively manufactured Mg alloys for biodegradable implant applications PhD position - Ad Print4Life DC12 - code no. 2025/MO 4
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1st, 2026 Work location: Geesthacht (near Hamburg) Application deadline: December 31st, 2025 EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization