62 parallel-and-distributed-computing-"UNIS" positions at Chalmers University of Technology
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Application Deadline 10 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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specialise in nanoparticles formulated from lipids. We characterise the composition and distribution of lipid molecules in both synthetic and naturally occurring nanoparticles (including extracellular vesicles
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motivated PhD candidates who want to enter a doctoral program at the forefront of science. Our PhD students develop abilities to plan, perform, critically review, and present their research. PhD studies
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We are looking for a motivated doctoral student who wants to explore how generative AI can transform the design of advanced heat exchangers for future aircraft propulsion systems. About the position The PhD position is part of a national project supported by VINNOVA under the Advanced...
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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 position within
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planning. The applicant should have computational competencies (including Excel and GitHub), be able to work in multicultural and interdisciplinary teams, and have excellent verbal and written communication
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spectroscopy for studying heterogeneity and radial depth distribution of modifications in intact fibers, as well as structural complexity in amorphous solid dispersions of pharmaceutical relevance. About us You
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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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into molecular structure-property relationships, and obtain understanding of chemical reactions. We frequently collaborate with colleagues from synthetic organic chemistry, computational surface science and
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actions to evaluate, balancing safety and computational effort. You will compare deep learning–based methods and probabilistic machine learning approaches, and explore extensions to active reachability