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by working on research projects in AI safety and robotics, contributing across the full research lifecycle: algorithm and system design, code development, experimental validation, and scientific
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of computer vision algorithms, with a focus on assessing performance in edge deployment settings. Their role will involve supporting model development, running experiments, and analyzing results to evaluate
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of computer vision algorithms, with a focus on assessing performance in edge deployment settings. Their role will involve supporting model development, running experiments, and analyzing results to evaluate
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algorithms for behavioral cue extraction and novel approaches for the modeling people interaction, with application to medical research and affective computing. Responsibilities: Write code and develop novel
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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Monitoring and Safety Evaluation - Develop algorithms for monitoring human actions during physical task execution using multimodal sensing (vision, pose estimation, and tactile signals). The candidate will
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records. Responsibilities: Assist in the research and development of a large model for 2D navigation. Design, execute, and document experimental evaluations to validate model performance. Design and
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Monitoring and Safety Evaluation - Develop algorithms for monitoring human actions during physical task execution using multimodal sensing (vision, pose estimation, and tactile signals). The candidate will
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Bachelor's Degree in Computer Science, Computer Engineering or a related field Experience in developing algorithms Experience in academic research and project work A combination of education and relevant
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members. Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous