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independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Effective communication skills and an interest in contributing to a highly international
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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, applied mathematics, neuroscience, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar
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tasks and zero-shot evaluation in linguistic analysis. Profile • Master’s degree (M2) or PhD in computer science, NLP, machine learning, deep learning, or a related field. • Strong experience in machine
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to live, learn and grow. Join us and contribute to our culture. Additional Information: Purdue’s benefits summary https://www.purdue.edu/hr/Benefits/ Purdue will not sponsor employment authorization
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
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and deep understanding of the global higher education landscape. The ability to thrive in a complex, fast-changing environment. The University of Leeds offers a range of benefits including excellent
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comparison to my peers. I am proficient in written and spoken English. During my courses or prior professional activities, I have gathered experience with machine/deep learning, and can demonstrate a strong
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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
Machine Learning (DM3L) Doctoral Candidate in computer vision and machine learning for developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources 80