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Field
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with molecular and clinical data, the work seeks to identify novel disease-associated features and translate these into clinically deployable models for improved diagnosis and prognosis. You will be of a
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: A PhD degree in chemical engineering, mechanical engineering, materials science, physics, or a related field. Demonstrated experience with molecular simulation and/or process modelling and simulation
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AI-driven decision making. It will be conducted in collaboration with the Automatic Control group (from Department of Electrical Engineering) and the Mathematical Optimization group (from Department
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the European Research Council. The project explores the relationship between digital technology providers and European welfare states in the context of data-driven innovation. The candidate will oversee the work
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
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place in a collaborative, mission-driven research environment that values technical creativity, rigorous engineering, scientific impact, and teamwork. The group works on practical AI systems that connect
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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3 Jul 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Programming Computer science » Other Engineering » Communication engineering
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system