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Field
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data to design robust, efficient deep learning algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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range of topics in deep learning theory and theoretical neuroscience. For more information and recent publications, please visit pehlevan.seas.harvard.edu . Successful candidates will have the opportunity
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Vacancies Postdoc position on deep learning based medical imaging for medical robot Key takeaways In this role, you will help develop and implement cutting-edge AI solutions for real-time, image
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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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and programming skills and experience of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience
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Additional Information Eligibility criteria Transversal knowledge required : - Expertise in machine learning and deep learning in particular - Knowledge in ecology, marine biology, or oceanography would be a
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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, and research team to ensure timely achievement of project deliverables. Undertake the following specific responsibilities in the project: i. Develop, train, and optimise deep learning models for object