471 gis-python "NTNU Norwegian University of Science and Technology" Fellowship positions
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and maintain Python and R codebase for transit routing and GIS operation automation. · Generate and write grant proposals with Dr. Liu on various topics. · Work with undergraduate and graduate students
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or a good honours degree in one of the above-mentioned disciplines with at least three years of research/relevant work experience. Applicants should also have: (a) proficiency in SPSS, GIS
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Engineering, skills in the areas of Geographic Information Systems, Geodesy and Hydrography. Additional optional skills and qualifications: Experience with GIS software and geospatial analysis tools. Experience
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project. You'll apply remote sensing and participatory GIS mapping to develop a framework guiding sustainable forestry investments. Working with leading institutions and industry partners, you'll have the
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optimization. Practical experience with industrial or collaborative robotic arms (e.g., UR, KUKA, ABB). Proficiency in programming languages such as Python, C++, and ROS. Experience working on interdisciplinary
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terms of publications Proficiency in scientific computation in C/C++ and Matlab/Python or similar languages Good communication and writing skills The College of Science seeks a diverse and inclusive
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, Extensive experience in building Neural Network models and a solid foundation in mathematics. Technical proficiency in Python, C, or C++, and familiarity with Tensorflow Lite/Micro, Pytorch. Experience in
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 4 days ago
machine learning-related discipline. Strong publication track record in top ML, computational chemistry, or computational biology conferences and journals. Proficiency in Python, demonstrated through
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Eligibility requirements for the position. Required Qualification: Ph.D. in bioinformatics, computational biology, statistics, computer science, or related field Proficiency in R or Python Minimum one year of
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software