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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 15 days ago
capable of advancing these topics independently. In close collaboration with experienced researchers, the engineer(s) will be in charge of: developing a data acquisition interface developing computer vision
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Science, or a related technical field Master's or PhD degree in Machine Learning, Computer Vision, or related areas will be advantageous Preferred Qualifications: Experience with biological/ecological
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learning systems, among others. Successful candidates will be responsible team players and passionate on cutting edge computer vision and machine learning technologies, as well as possess deep understanding
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vision techniques. Additionally, the hired student will assist in corrosion/surface defect detection, object tracking of moving targets, and other machine learning based tasks. The computer vision team
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Deep Learning libraries (e.g., Pytorch, Tensorflow, Keras) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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Position Details Position Information Job Title Computer Vision Developer Appointment Type Student Employee Job Location Corvallis Position Appointment Percent 100 Appointment Basis 12 Pay Method
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-of-the-art machine learning and computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering, computer science or mathematics (or a related field), with a focus
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the majority of immune cell types. The multi-scale computational model integrates mechanistic molecular and cellular-level models with population whole-body models, utilizing machine learning and distributed
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their field of view, guided by their gaze. The success of this project will be critically dependent on the contributions of a researcher with expertise in human and machine vision. Qualifications The ideal
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at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and computer vision for the life sciences Your Profile: Excellent Master’s degree in engineering