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supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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the development and optimization of products for a variety of industries from automotive to aerospace made from new bio- and waste-derived plastic resins and fillers. The ideal candidate for this role would be
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for scientific computing and high-performance computing environments. Develop and evaluate optimization techniques for machine learning workflows, including approaches for model tuning, automated model design, and
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Application Deadline 27 Sep 2026 - 23:59 (Europe/Warsaw) Country Poland 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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optimization and consensus algorithms. Knowledge of large models and hyper-parameter optimization. Knowledge of high-performance computing and its applications. An excellent record of productive and creative
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. The project will involve drone optimizations, computer vision, closed-loop control, multi-modal sensor fusion, machine learning, and transfer learning methods. The candidate will also work in collaboration with
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optimization of advanced energy storage systems utilizing coal-derived and other carbon materials as battery electrodes. The successful candidate will conduct experimental research spanning materials development
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integration. Investigate how traction grids can support high-power charging at construction-sites though optimal sizing of chargers and mobile battery storage systems based on the demand and through energy