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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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datasets, and synthesize results for publication and reporting. Proficiency in programming languages and software commonly used in research, such as Python, MATLAB, R, or GIS tools. Excellent written and
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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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: · 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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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours 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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for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical, chemical, and biological components into the river-lake network models
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in data analytics and statistical methods, particularly using tools such as R, Python, or other relevant software. Experience with Data Visualization & Programming: Expertise in data visualization
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
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technologies and methodologies, and Geographic Information Systems software (e.g., ArcGIS, QGIS), Python, and Matlab is required. Knowledge of other programming languages (e.g., C, C++, R, Javascript) is
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to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big