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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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at the Department). The PhD-project will be connected to the research group of Prof. Nathalie Reuter at the Department of Chemistry and the Computational Biology Unit , in collaboration with Prof. Odd André Karlsen
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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for academic development through a PhD education leading to a doctoral degree. The hired candidate will be admitted to the PhD program in Arts and Education. The education includes relevant courses amounting
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Intercropping of cover crops and vegetables to mitigate nitrate leaching and improve soil health in organic farming Applicants are invited for a PhD Fellowship/Scholarship at Graduate School
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papers Contributing to quarterly and annual report writing and presenting Job Requirements: PhD degree in Artificial Intelligence, Computer Science, Software Engineering Strong background and research
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employment period is three years. A premise for employment is that the PhD Research Fellow will be enrolled in USN's PhD-program in Technology within three months after accession. About the PhD-project
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics