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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 15 hours ago
metabolomics] research, with experience in the use of techniques in machine learning, statistics, algorithm engineering, bioinformatics, or advanced data visualization. Evidence of effective participation and
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 15 hours ago
-level service activities. Promote an inclusive and supportive learning environment for undergraduate students. Qualifications: A PhD in Electrical and Computer Engineering or a closely related discipline
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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experience in optimization, machine learning, control systems, or robotics is desirable. No other specific qualifications beyond and a willingness to learn within an interdisciplinary team. If you have any
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, research areas include Operations Research, Information Engineering, Human Factors, and Applied Machine Learning, all of which seek to improve the systems we as humans rely on to navigate our world
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series analysis, machine learning approaches). Ability to apply data analysis and simulation skills to generate insights into operational changes or targeted retrofits that will enhance building energy
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in the laboratory QUALIFICATIONS Successful applicants will have: PhD with expertise in cancer biology, proteomics and/or computational biology / machine learning A proven track record with first
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for this position are as follows: PhD in Forest Ecology, Entomology, or a closely related field, with a focus on geospatial modeling, invasive species dynamics, and applied machine learning for pest risk assessment
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of Professor, with an anticipated start date of July 1, 2026. We seek candidates conducting research on climate data science that draws together observations, models, and machine learning. Candidates must have a
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(inclusive of PhD and/or post-graduate work) in accelerated research and development in the area of development and application of machine learning/deep learning methods for biological or chemical data