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biomarkers associated with adverse pregnancy and neonatal outcomes. Apply statistical modelling, machine learning, network analysis, and systems biology approaches to large-scale datasets. Perform longitudinal
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an industry partner. Experience with research software, data pipelines, and simulations, machine learning, high-performance computing, CANFAR, or advanced data systems. Evidence of mentoring or supervising
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environments that aims to address how distributed sensing, fibre-optic monitoring, environmental observations, drone- and satellite-based data, operational infrastructure datasets, and/or machine learning can be
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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30th September 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in climate data analysis and machine learning emulation of hydrological models Apply for this job See
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: Guide junior researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming
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quantitative genetics, Bayesian methods, machine learning, large-scale genomic datasets, single-cell omics or integrative omics analyses would be highly regarded if the candidate was not initially trained in
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the
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. Advanced machine learning, reinforcement learning, and agent-based optimization techniques will be developed to reduce voltage deviations, cut active power curtailment, and improve system adaptability under
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno