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machine learning models, and develop a generalizable decision-support system for vehicle and station allocations. This research will be conducted together with domain experts and collaborators. The research
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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects
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experimental and simulated data, leveraging AI and machine learning techniques Contribute to novel computational optimisation methods for machining processes Develop and implement automation solutions, including
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for nowcasting, high-frequency indicators construction, machine learning, time-series econometrics and maintains the data and tools that feed the regular KOF macroeconomic forecasts. Curious? So are we. We look
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scientist holding a PhD in physics or astronomy, with a strong background in software development and machine-learning applications, demonstrated through contributions to open source projects and production
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, qualitative methods that combine situated ethnographic detail with deep knowledge of cultural and political contexts and histories, ideally in a cross-national comparative perspective. You can learn more about
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. Profile Applicants must hold a M.Sc. Diploma (120 ECTS points) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, computer sciences or related fields
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change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits
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only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide
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Researcher or experienced Data Scientist to harness AI, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental