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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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helping your colleagues. The group is part of the Section for Experimental and Translation Immunology at the Department of Health Technology . Our section has all the necessary infrastructure and comprises
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. Cox. The position is available starting 1 December 2025. The successful candidates will work on developing new theoretical models and computational methods to investigate the emergence and properties
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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Key Responsibilities (in close collaboration with TU Munich): Develop a deep understanding of materials engineering principles to guide the design and functionalization of nanoporous materials
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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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engineering challenge. Key to success will be the development of cost competitive and reliable methods to produce hydrogen via electrolysis of water/steam driven by green electricity. Hydrogen can be used as a