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Field
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intelligence. This part focuses on robotic agents operating in unstructured 3D environments (homes, offices, industrial sites, shopping malls). The work centres on (a) model-based and hybrid RL algorithms built
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and human-based leadership. As organizations increasingly blend algorithmic and human decision-making, fundamental questions arise about how leadership operates, adapts, and creates value in this new
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-camera, home-based markerless system Test the algorithm across lab and home-recorded environments to assess real-world performance Design clinician-facing visualization tools ensuring privacy-by-design
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research and implementation. You will also develop novel algorithms using state-of-the-art computer vision and machine learning techniques (segmentation, multimodal AI, foundation models, agentic frameworks
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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, including bioacoustics algorithms developed in the team. What you will do Conducting rigorous research at the intersection of ML and wildlife bioacoustics; Actively participating in regular group and one
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algorithm design skills Expertise on ML tools for chemistry, in particular, generative AI Experience with Python, ML, and AI for chemical applications Job Description: A Post-doctoral Associate in Theoretical
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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experimental cycle from real-time X-ray measurements to post-experiment reconstruction: Develop learning-enabled algorithms for 3D reconstruction of noisy and heterogeneous synchrotron datasets. Implement