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analytical models Physics-informed machine learning for deformation modeling and prediction Integration of perception, planning, and control for robust real-time robotic performance Requirements Ph.D. in
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and reality gap bridging for deformable object interaction (e.g., MuJoCo, PyBullet, NVIDIA Isaac Sim) Adaptive feedback control using learned and analytical models Physics-informed machine learning
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio
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