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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in programming languages/software such as MATLAB, Python, R, Stata, as well as GIS
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develop an end-to-end processing system as well as a hazard map visualization (Web and/or GIS); Publishing the various scientific advances in conferences and peer-reviewed journals. Where to apply E-mail
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programming languages/software such as MATLAB, Python, R, Stata, as well as GIS applications (e.g., QGIS). Have excellent communication skills in both English and Chinese, in writing and in oral presentations
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, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research partners on campus at the UO, with
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processing environmental exposure and health administration data via Application Programming Interfaces (APIs) proficiency using statistical programming software such as R, SAS, STATA and Python; and GIS
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will have a background in computer/data science, and specifically have computer programming experience, working with programming languages such as Python or R, in order to develop and maintain data
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 36 minutes ago
geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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statistical modelling, Solid skills in computer programming for data science (e.g. R, Python), Experience with real-world data analysis tasks, Good communication skills in English, both verbal and written