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sciences Economic and Administrative sciences Maritime sciences Social sciences and Humanities. The Faculty is also responsible for PhD programmes in computer technology, innovation and regional development
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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research in system and circuit design for next generation wideband radio frontends. The position allows access to fabrication in multiple semiconductor technologies provided by international partners inside
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty