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combinatorial, algebraic, and probabilistic tools, you will work on resolving fundamental extremal problems in the area of finite geometry. These problems have connections to Ramsey theory, coding theory, and
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Group in the Social Networks Lab at ETH Zürich is developing network data science methods and applying them in a variety of domains. Our current research focus is on sports analytics and we seek to expand
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Doctoral Candidate positions of the EIFFEL (EffIcient Fullerene-Free organic solar cELs) Doctoral Network, which focuses on the development of efficient NFAs, revealing the mechanisms of operation and
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professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): go.fzj.de/JuDocs 30
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families (e.g., generative models or graph/equivariant neural networks) to accelerate candidate discovery and hypothesis generation. Disseminate research findings through publications, conference
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high infrastructure costs. We will explore (1) learning-based techniques (e.g., LLMs, agents) to capture the intent behind code changes, (2) defining new metrics for test "quality" that go beyond code
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Delft about the new insights we gather. We will focus on open science, sharing our results to help developers across the world. Automated Code Refactoring The focus is on exploring and evaluating
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/MSCA fellow for the project: “The impact of menopause transition on women’s brain health with focus on AD risk.” The position is part of the EU-funded Marie Skłodowska-Curie Actions Doctoral Network
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battery for thermal storage. The idea is to combine waxes obtained through pyrolysis of plastic waste streams, with ultra-conductive graphene networks, i.e., nanometer sized carbon platelets that transport
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: Dr. Bloemendaal). You will be part of a unique team of interdisciplinary researchers, with access to an international network in fields of psycho-neuro-immunology and the gut-brain-axis. The Department