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formal methods. The successful candidate will contribute to advancing data-driven modeling techniques that enable formal safety guarantees for complex dynamical systems such as autonomous vehicles
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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The »Grid-free Methods« department at the Fraunhofer Institute for Industrial Mathematics ITWM focuses on the modeling and efficient simulation of complex industrial problems for the design and
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Computational modelling of two-dimensional graphene-based materials School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline
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19 Mar 2026 Job Information Organisation/Company University of Antwerp Research Field Computer science » Other Engineering » Electrical engineering Engineering » Other Mathematics » Applied
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for further, more detailed analysis. Research areas include, but are not limited to: Incorporate resilience research [e.g., 2, 3] into extensions of the mathematical programming model underlying NIST ARC so as
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: The Mathematical Sciences Department offers undergraduate, Master?s, and Ph.D. programs in pure, applied, and computational mathematics. Research across a variety of disciplines is strengthened through
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, Mathematics, or closely related fields. • Experience conducting experimental, theoretical, or computational research. • Familiarity with mathematical modeling, data analysis techniques, or computational tools
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candidates for this project should have a strong background in Applied Mathematics, Engineering, Physics or other related disciplines. Full details of how to apply can be found at the following link: https
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The candidate must have a strong background in algorithmics, optimization, and data science. In particular: Mathematical modelling: ability to formalize real-world personnel scheduling problems, including