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the soil-water-plant-air continuum using process-based models. You will learn how to take proper soil, plant and air samples that influence carbon and nitrogen dynamics and learns how soil and plant
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areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and
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Responsibilities: To independently undertake research in machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community
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conferences. About You You will be educated to doctoral level in Remote Sensing, Geography, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning or a related discipline. You will have
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of multi-modal datasets, including MRI/fMRI, behavioural and audio data Develop reproducible statistical and machine learning analysis pipelines Support grant writing, ethics submissions and project
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Abilities: Proficient in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive experience in libraries and frameworks such as Pandas, NumPy, scikit-learn, Gensim, BERTopic
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; · Perform other duties and provide additional support as assigned. Knowledge, Skills, and Abilities: Proficient in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive
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. Knowledge, Skills, and Abilities: Advanced in data analysis, modeling, machine learning, and AI, using Python and SQL, with extensive experience in libraries and frameworks such as Pandas, NumPy, scikit-learn
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, including data analysis and visualisation, machine learning, computational methods, and more. If offered the position, you will participate in the following projects, based on your background and strengths
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Postdoctoral Fellow in Machine Learning and Digital Health Services for Frail Older People Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile