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Field
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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with comprehensive baselines and validate results Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical
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proficiency in machine learning, statistical modeling, and data analysis using Python, R, or similar platforms. Experience in grant proposal writing, scholarly manuscript preparation, and psychological
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data, log-trace data from learning platforms, and panel data. Relevant areas of expertise include longitudinal data analysis, psychometrics, learning analytics, and machine learning. We are particularly
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in
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, collecting and analysing experimental and operational data, evaluating machine performance, and preparing high-quality technical reports for industrial partners. The Research Fellow will also be expected
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quantum chemistry, experience with machine learning regression methods. Preferred start date as soon as possible but flexible. Basic Qualifications PhD in Physics, Chemistry, Materials Science, Computer
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research grants in the above areas Job Requirements: A PhD degree in Computer Science, Data Science, Engineering, or a related field. Research experience in Computer Vision, Image Processing, Multimedia
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The position An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology . Goal: Develop
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune