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. The position aims to investigate the fundamental physical and chemical processes underlying the thermal-chemical conversion of green fuels, using advanced high-performance computational methods. The research
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structured manner. The role requires a high degree of personal maturity, confidence, and professional integrity and confidentiality. The job involves frequent contacts and co-operation with managers and
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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AI training has emerged as the standard approach, which utilizes thousands of high-performance devices within a data center to collaboratively process tasks. When they are even more complex, the
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This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The
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Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics” - a multidisciplinary research effort at the intersection of machine learning and materials science. This
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of classical circuit approaches. The main research area will lie in the improvement of dynamic range without increased power consumption. Here you will perform research ideas combining multiple LNAs and ADCs
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universities. About the research project This PhD project is part of the interdisciplinary WASP-WISE NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through
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working in Unix/Linux environments and high-performance computing (HPC) systems (e.g. SLURM etc.). Excellent communication skills in both written and spoken English are required, as is ability
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build the sustainable companies and societies of the future. The Robotics and Artificial Intelligence subject, RAI, at the department of Computer Science and Electrical and Space Engineering at Luleå