66 parallel-computing-numerical-methods-"Simons-Foundation" positions at Chalmers University of Technology in Sweden
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properties. Advanced characterization methods and development of new techniques – We specialize in hyphenated rheological methods such as rheo-SAXS and rheo-DES, which are primarily applied to materials like
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The PhD student will join a world-leading research environment at the Chalmers Security and Privacy Lab . Software is often the root cause of vulnerabilities in modern computing systems. We develop
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ocean, and an urgent need to inform regulatory bodies about associated environmental risks. The work builds upon methods developed in our previous inter- and transdisciplinary work on shipwreck risk
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Computer Science and Engineering is strongly international, with approximately 300 employees from over 30 countries. The department is a fully integrated department with Chalmers University of Technology and
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6 Sep 2025 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Other Engineering » Materials engineering Physics » Other Researcher Profile First
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16 Nov 2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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the application of machine learning to optics, touching upon aspects of computational electromagnetism and inverse design. Information about the project and division Structured optical materials, such as
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Application Deadline 1 Nov 2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Doctoral student in Materials Chemistry of Doped Organic Semiconductors in EU Training Network FADOS
Researcher (R1) Country Sweden Application Deadline 6 Oct 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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advanced data-driven methods. This is a unique opportunity to contribute to pioneering research that tackles one of today’s most pressing challenges: how to design resilient, secure, and reliable network