2,797 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
Postdoctoral Trainee - Carolina Cancer Nanotechnology Training Program (Postdoctoral Scholar) Vacancy ID PDS004223 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC
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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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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
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computer science, operations research, applied math, statistics, or a related field Strong background in machine learning, optimization, and/or algorithm design Excellent written and verbal communication skills
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docking and machine learning. Among the key duties of the position are the following: Performs various research and technical operations relative to ongoing investigatory activities of a laboratory; may
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, industrial energy systems, energy efficiency of manufacturing industry, or other related fields. You will play a crucial role in the planning, execution, and optimization of our technical assistance program
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score derivation and validation, and other relevant analyses. Develops R or Python scripts for data analysis, statistical modeling, and machine learning techniques, ensuring reproducibility and efficiency
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race in national or global contexts and, with the approval of the Office of the Dean of the Faculty, will teach one semester-long undergraduate elective course. During the semester of teaching
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employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of