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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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development and implementation of deep learning models and robotic systems for the automated analysis of multimodal ophthalmic imaging data e.g. Optical Coherence Tomography (OCT), fundus photography, etc.; (b
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hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
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their research data with a specialized focus on the Health Sciences. You will be an important member of the Deep Blue Repository & Research Data Services (DBRRDS) team and contribute to all aspects of its work
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the AI and Deep Learning team, this internship is designed to provide hands-on experience at the intersection of science and advanced technology. The specific project will be tailored to the aptitude
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Offer Description In recent years, hardware architectures for embedded AI (particularly in the area of Deep Learning) have become extremely modular and heterogeneous, while retaining high flexibility
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qualifications and experience as they relate to this position. Please include a description of one related deep learning model or framework (e.g., AlphaFold, ESM, Chai-1, Boltz-1, etc.) that you have used. Briefly
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Responsibilities: To conduct independent research in deep reinforcement learning and large language models. To produce publications in top conferences and journals. To offer guidance and assistance to any students
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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programming languages like C and Python, as well as deep learning frameworks such as PyTorch and TensorFlow. Knowledge in imaging and computing device and equipment. Strong communication, organizational, and