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Field
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environments that aims to address how distributed sensing, fibre-optic monitoring, environmental observations, drone- and satellite-based data, operational infrastructure datasets, and/or machine learning can be
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, Computer Vision, or related areas, accompanied by enrolment in a doctoral programme in relevant areas, or by a commitment to submit proof of enrolment and registration by the scholarship contracting stage
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and capability gaps. Learning Objectives: Through this opportunity, you will gain knowledge and practical experience in biosurveillance, emerging biological threats, public health preparedness, program
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researcher in Computer Science, Data Science, Human-Computer Interaction, Psychology, Empirical Educational Research, Learning Sciences, Cognitive Science, or related disciplines who is eager to contribute
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robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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Institutions. Preference factors: Previous experience in biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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Understanding of & ability to contribute to broader management/administration processes Experience developing & applying machine learning models to computer vision tasks Practical experience in computing
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description NOMIS Foundation ETH Postdoctoral Fellowship The NOMIS