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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 10 days ago
modules leveraging deep learning for classical problems such as segmentation and 3D object tracking interfacing machine learning code and the robot using ROS2 contributing to the creation of datasets
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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mechanics, finite element modeling, and scientific machine learning. The RSE will contribute to the design, implementation, and maintenance of open-source software libraries that integrate phenomenological
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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Scene Understanding Detection and Identification of Objects (SSUDIO) project. The purpose of this project is to develop scene understanding from 3D scans of ships by applying machine learning/computer
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into actionable insights, novel tools, and impactful research outcomes. Key Responsibilities Develop, implement, and optimise AI/ML models (artificial intelligence/classical machine learning, deep learning
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. Ability to learn and apply complex policies quickly, including admissions, financial aid, and military education procedures. Demonstrated ability to build positive professional relationships with diverse
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
(SHRA) Position Title UTS - Temporary Computer Technician- Inspection and Customer Support at UNC Chapel Hill Position Number Vacancy ID S026725 Full-time/Part-time Full-Time Temporary Hours per week Work
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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: Monday – Friday, 8 a.m. – 5 p.m. Summary The Michael E. DeBakey Department of Surgery is seeking a Research Associate to implement and maintain the ATLAS (Applied sTatistics and machine Learning