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computing and machine learning is available at the Department of Data Science at the Faculty of Science and Technology . The PhD position is for a period of 3 years. Desired start date: within 1st September
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for more than 10 years. A comprehensive approach will be achieved through collaboration with ecologists (Applied Quantitative Ecology Group at MINA), data scientists (Machine learning at Faculty of Science and
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we will apply state-of-the-art machine learning and deep learning techniques on open- access and collected datasets to determine how accurately these systems can identify dock plants under Norwegian
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(AI) including predictive machine learning models, risk assessment techniques, and multi-objective optimization. The research will integrate AI-driven predictive and prescriptive approaches, focusing
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relevant education corresponding to a five-year master’s degree or a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle
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experiences and skills will be emphasized: Desired knowledge/experiences in: Working with diverse remote sensing data Data science topics particularly machine learning and deep learning. High Performance
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of mobile robot navigation principles Strong skills in data analytics, computer vision and machine learning Skills in scientific writing Applicants who have recently graduated with excellent results may be
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Applied ecology PhD: Large carnivores in Scandinavia from individual movement to population dynamics
) in Scandinavia. You will develop and apply integrated models combining spatial capture-recapture and GPS data, working with a diverse team of ecologists, statisticians, and computer scientists from