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, and productivity in research, the strong potential to obtain external funding, a capacity for excellence in teaching and mentoring of undergraduates, graduate students, and postdocs, and a commitment to
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Nature Careers | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 21 days ago
learning, statistics, algorithm engineering, bioinformatics, or advanced data visualization. Evidence of effective participation and leadership roles in interdisciplinary research teams, teaching, and
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preferred. Experience utilizing computer vision algorithms and frameworks, including medical image classification, feature matching, edge detection, image segmentation, and deep learning models like
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ecosystems. Fairness, safety, interpretability and trust in AI algorithms and AI-based technologies. Applications with healthcare, energy, sustainability, business analytics, etc. Candidates are expected
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both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate
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revisit discretization methodologies in view of modern requirements and computational capabilities. The candidate will focus on developing mesh generation algorithms meeting the following criteria
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RNA-seq datasets and generate user-friendly applications for data exploration; to perform data analysis derived from diverse scientific topics in collaboration with PhD students and postdocs; to train
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, Environmental Science, or related disciplines Proven expertise in environmental science and data-driven research as PostDoc Experience in acquiring third party funding in the relevant fields of data science
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profile PhD in an environment-related field followed by experiences as PostDoc in related interdisciplinary research contexts, optimally with research that aimed to work on environmental evidence synthesis
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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides