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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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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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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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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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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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ability to conduct archival research on English materials ranging from 1300-1950; Experience working with large quantities of data and/or with databases; Excellent organisational skills; The ability to work
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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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series of wind/solar power production, as well as NWP outputs (big data), the candidate will focus on the development and testing of new forecasting models, with especial emphasis in novel AI-based methods
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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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. You feel confident to work with big data and present the findings in a clear and concise way. You hold a Master's degree, preferably in Finance, Economics, Econometrics, or related fields, and are