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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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to cutting-edge tools, algorithms, and large, high-quality seismic datasets. Occasional fieldwork to acquire data from temporary networks, providing you with hands-on experience in the field. A competitive
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business applications. Profile Required Qualifications Master's degree in Computer Science, Data Science, or a related technical field with strong foundations in machine learning OR Master's degree in
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scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Required Skills: Strong analytical background Proficiency in geometric deep learning and machine learning Prior experience in physics-informed
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implementation of machine learning. PhD student position in the field of durability of wooden structures Your tasks Your tasks will focus on the design and operation of experiments to investigate the failure
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degree in Computer Science, Data Science, or a related technical field with strong foundations in machine learning OR Master's degree in Mathematics, Statistics, Physics, or other quantitative discipline
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related field. Programming, modelling, and data analysis skills in python and machine learning/optimization libraries/toolboxes support you in contributing to our ongoing software development efforts. Your
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related to staff position within a Research Infrastructure? No Offer Description PhD Position in Decentralized Resource-Constrained Machine Learning The Distributed Computing (DISCO) Group is a research
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11 Feb 2025 Job Information Organisation/Company ETH Zürich Research Field Architecture » Landscape architecture Architecture » Other Engineering » Other Environmental science » Other Geography
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) Experience with simulation programs, big data analyses, or qualitative analyses. N.B. it is not expected/desired that you have experience with all of these methods/programs, but familiarity with some are