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,3 ,4 ,5 ). The group has worked on a large variety of viral and bacterial pathogens of humans and animals and uses mostly E.coli, bacteriophages and plasmids to study epidemiological and evolutionary
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operated by ETH Zurich and has offices in Lugano (headquarters) and Zurich. Project background As HPC and cloud technologies converge, CSCS strives to improve its service portfolio that focuses on large
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. Profile The ideal candidate will be a computer science student or a student with extensive practical programming experience. Interest in the social sciences and law is a big advantage. Workplace Workplace
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understanding of the past. This doctoral project aims to integrate diverse historical resources—primarily maps and texts—to enhance spatio-temporal information retrieval using GeoAI and Large Language Models
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of large data analyses as well as very good English language skills are mandatory. Knowledge of the German language and experiences with stakeholder interactions are a plus. Workplace Workplace We offer Your
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candidate with a strong background geology/geomorphology, or a related discipline, a strong interest for evolutionary biology, and who is interested in bridging field data, computational modeling, and large
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for decentralized and distributed data-driven methods for Federated Learning on resource-constrained networks. Your research within the project will contribute towards your doctoral degree at ETH Zurich. You will be
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university near Zurich. You have an interest in law or policy diffusion, privacy law, and international comparative law. Knowledge of privacy / data protection law is highly desirable. You have excellent
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, data science, and industrial applications. As part of this position, you will: Develop and implement advanced Machine Learning models to analyze large datasets, including image and time-series data
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imaging, single cell tracking and quantification, large volume 3D bone marrrow imaging with single molecule sensitivity, and ai-supported computational analysis. Job description We are seeking a highly