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Field
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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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-genome deep-sequencing data collected as part of the Office for National Statistics Covid Infection Survey, with a focus on using household data to enable methods for determining who-infected-whom using
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., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc. Experience of working with molecular questions in the biosciences An interest and
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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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(or near completion) in computer science, machine learning, statistics/biostatistics, computational biology, data science, physics, or a related field. Experience with modern deep learningframeworks (e.g
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Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g
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applying causal inference, spatial econometric modeling, and machine learning techniques to questions of regional economic development, urban sustainability, or entrepreneurship ecosystems. Proficiency in
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning