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Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on
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of fungal networks, but also strengthens advocacy for these essential organisms in global sustainability and soil health research.' Vasilis Kokkoris, Assistant Professor, Amsterdam Institute for Life and
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will be part of a leading team in network data science within the Multimedia Computing Group (MMC) in Computer Science. We share a drive to understand and optimize complex systems ranging from social
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synthesise complex evidence into clear scenarios and practical outputs that support workforce development and strategic decision-making. Beyond your research, you will contribute to academic publications and
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of high‑tech system design—such as the design of lithography machines—can already be automated, current design‑automation tools remain limited to specific domains or subsystems. Given the growing complexity
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companies and asset owners. International collaboration and industrial workshops are embedded in the project, providing you with excellent exposure and networking opportunities. Job requirements You are a
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, defect localization, temporal reasoning, and predictive maintenance in complex inspection environments. A second contribution involves predictive maintenance algorithms that integrate static data sources
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into complex tissue-like structures. These structures offer exciting opportunities to mimic organ development and embryogenesis in vitro. However, current organoid models still only partially replicate natural
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validation. Within the PRECISE consortium, you collaborate with a multidisciplinary national network. You contribute to genotype-specific target validation, participate in the PRECISE Early Career program, and
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engineering using genetic modification can solve some of these problems, but introduces regulatory complexities and biological challenges of it’s own. Epigenetic editing, the controlled reprogramming