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of Immune Engineering (BIIE), which aims to develop innovative computational and immune-based solutions for pressing health challenges, particularly those affecting children and adolescents, and encourages
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The multilateral system is entering a decisive decade. Scientific and technological breakthroughs are reshaping societies, economies and ecosystems faster than governance can respond. Diplomats are asked to negotiate rules and anticipate the impacts of innovations that can barely be tracked,...
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DIZH understands innovation very broadly and includes all disciplines: artistic, design, natural science, technology, humanities, education and social science.
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-dimensional datasets. Your profile • PhD in neuroscience, computational neuroscience, or related quantitative discipline (neuroscience background required). • Strong expertise in neuronal data analysis (spike
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Your position We're strengthening our team to deliver on our core mission: helping entrepreneurs turn ideas and discoveries into successful startups. We're looking for someone with both experience and enthusiasm for designing and running high-quality programs and for creating opportunities that...
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competitive grant proposals to support independent and joint research activities. Where to apply Website https://apply.refline.ch/673278/3852/pub/en/index.html Requirements Research FieldPhysics » Computational
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Department of Pathology and Molecular Pathology Non-Tenure Track Assistant Professorship of Computational Functional Tumor Pathology 100% Start of employment by agreement, temporay The Faculty
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12 Dec 2025 Job Information Organisation/Company University of Basel Research Field Biological sciences » Biology Computer science » Other Mathematics » Statistics Neurosciences » Neurology
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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-facturing processes. In this internship, you will work on state-of-the-art anomaly detection methods using computer vision and time-series data, with a particular focus on multimodal data fusion for powder