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candidates with a degree in materials science, solid state chemistry, electronic engineering or similar. Experience with one or more of the following areas is considered an advantage. Fuel cells and
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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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, building energy and installation, solid mechanics, fluid mechanics, materials technology, manufacturing engineering, engineering design and thermal energy systems. Technology for people DTU develops
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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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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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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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. 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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) therapy on the biology of γδ T cells and how can we use this knowledge to help us predict the success of therapy and prevent the development of side-effects. Position 1 will focus on the cellular and
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. The overarching goal of this newly funded project is to realize quantum light sources coupled to quantum memories. Quantum memories are key components of optical quantum computers and scalable quantum networks