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UNIX/Linux interface and basic programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be
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programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be able to work independently and in a
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high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD candidate for this position will work within the scope of the project
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project/work tasks: The SnowAI project aims to use to produce new high-resolution datasets on snow depth in Western Norway derived from machine learning and radar remote sensing. The successful PhD
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. Conceptually, this includes data from a single experiment (regularization), across two experiments (registration), and for analyzing large datasets (statistical analysis and machine learning). This development
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at https://cbu.w.uib.no/joshi-group/ . Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr. The core
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Science) in a uniquely interdisciplinary environment. The project will be supervised primarily by Professor Anagha Madhusudan Joshi-Michoel, who specializes in applying machine learning and data science
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synthetic steps (and routes), using machine learning in closed-loop (autonomous) optimizations. The tasks will be varied, and you will have the opportunity to contribute to developing new solutions in a
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be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience
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. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience with programming and app development will be emphasized The LEAD AI mobility