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PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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master in Computer Science, Bioinformatics or related field Strong programming skills in R Background in machine learning and/or protein structures Fluent in English Specific Requirements Mobility rule
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references: Ajay K. Agrawal, Joshua S. Gans, and Avi Goldfarb. 2019. The Economics of Artificial Intelligence: An Agenda. University of Chicago Press. McAfee, A., & Brynjolfsson, E. (2017). Machine, Platform
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developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with the running infrastructures. Using
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, and communicate complex spatial environments? Do you hold a master’s degree in cognitive science, environmental psychology, human-computer interaction, geo-information science, or a related field, with
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results in scientific journals You contribute about 10% of your time to teaching and supervising in bachelor and master programs Where to apply Website https://www.academictransfer.com/en/jobs/362571/phd
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@aalto.fi . In any question regarding the recruitment process, please contact HR Advisor, [email protected] . Learn more about the TSirc research group: https://kwantaekim.github.io Want to know more about us
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or complementing traditional physics-based approaches by data-driven ones, using Machine-Learning (ML). Such approaches allow enormous gains of time, in a way that can be related to the astonishing efficiency
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Systems conducts research and education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Read more about us here: https://liu.se/en