23 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Norway
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data, MRI data, and other types of data. Contribute to projects at LCBC with data analysis, development, and implementation of advanced machine learning models. Write and publish scientific articles
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engineering and science, as well as PhD education in computer technology. The Mohns Center for Innovation and Regional Development researches innovation and offers master's education in innovation and
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data collection approaches. Familiarity with or strong motivation to learn machine learning or advanced data analytics for pattern detection and forecasting in environmental data. Familiarity with
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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work
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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration
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. Your main tasks will be Develop and apply machine learning techniques and statistical analyses, including novel methodology for analysis of complex polygenic traits and prediction tools for precision
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of the Arctic Geology Department . Qualifications Required Qualifications A PhD in Geology, Earth Science, Geophysics or a related field that involved numerical modelling of glacial or permafrost mechanics and/or
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. Applicants must have submitted their PhD thesis to the PhD evaluation committee when sending the application. Appointment is conditional on having successfully defended the PhD thesis. The candidate´s PhD
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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candidate must have a PhD in ocean biogeochemistry, chemical oceanography, physical oceanography, ocean science, or similar field. Qualifications, skills and abilities Strong understanding of ocean