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Field
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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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on the design and development of mechanically intelligent surgical tools that simplify surgical motions and incorporate image sensing. These tools will be integrated with robotic platforms and machine learning
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) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5, Franka Emika
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Explore machine learning approaches for discovering interpretable and clinically relevant visual representations.; • Validate the proposed methodologies
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Osmosis (NF/RO) Membrane for Industrial Separation and Purification Application” Key Responsibilities: Integrating Machine Learning (ML) with Molecular Dynamics (MD) to predict phase-separation dynamics and
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position is available for the research on theoretical and numerical methods related to any of the following: open quantum systems, quantum information processing and quantum machine learning, nonlinear
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managing social media datasets and metadata from the 2020 and 2024 US Presidential elections and the 2024 UK General Election. Designing, implementing and evaluating NLP and machine-learning approaches
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areas: wireless security, wireless communications, AI/machine learning for communications, covert communications, signal processing, and/or RF design. Ability to conduct research independently and
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submitted. If email is not received, check the junk folder before contacting ORISE to confirm submission. To apply and learn more about EIF and host institutions – such as eligibility, requirements, and
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computer science. About the Group The Data Intelligence Group at UM6P-CC is a growing and supportive team with internationally recognized expertise in data management and machine learning. The group has a