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As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
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, it has matured into an established research community seeking automatic, computerized processing of 3D geometric data obtained through measurements or designs. The following developments have shaped
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computers, and especially fault-tolerant quantum computers, for high-value decarbonisation use cases such as improved battery chemistries, the development of new catalysts for hydrogen, biofuel or ammonia
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, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured light-trapping
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides
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experimental neuroscience aimed at advancing our understanding of memory and its disruption in aging and disease. AREAS OF RECRUITMENT Computational Neuroscience We seek exceptional scientists developing
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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and interpretation. Prominent examples include time sequences on groups and manifolds, time sequences of graphs, and graph signals. The objectives The project aims to develop unsupervised online CPD