48 parallel-computing-numerical-methods positions at Chalmers University of Technology in Sweden
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research group that views automation engineering as a key enabler for new methods and applications, driving and benefiting from the ongoing digitalization of society. Our research emphasizes social, economic
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the work will be detailed catalyst characterization. A wide range of methods will be used, including XRD, BET, SEM, TEM, TPR, TPD, DRIFT, and XPS. Atom Probe Tomography (APT), with sample preparation
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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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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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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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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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Application Deadline 4 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 programme Reference Number 304--1
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Sweden Application Deadline 9 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 programme Reference
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control and its integration with learning-based motion prediction under uncertainty. - Validate methods through simulation and collaboration with industrial partners (Volvo Cars and Volvo Group). - Publish