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Infrastructure? No Offer Description The Department of Computer and Systems Sciences. With over 200 employees and 4,500 students, the Department of Computer and Systems Sciences (DSV) is a strong and dynamic
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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at Master’s level in Mathematics, Computer/Data Science, Computational Science and Engineering, or a related field, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through
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cent of full-time. Your qualifications You have graduated at Master’s level in Mathematics, Computer/Data Science, Computational Science and Engineering, or a related field, or completed courses with a
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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the position and why you are especially qualified for it. Your workplace You will be employed in the Reasoning and Learning Lab (ReaL), Division of Artificial Intelligence and Integrated Computer Systems (AIICS
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at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science . At STIMA we conduct research and education in both statistics and machine learning