628 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Uk
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.) if candidate holds a relevant degree and is working on PhD/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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Fixed-term: The funds for this post are available for 12 months. Applications are invited for a Research Assistant (RA) to join the Prorok Lab in the Department of Computer Science and Technology
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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Aalto University is looking for an Postdoctoral Researcher in Artificial Intelligence / Machine Learning Engineering [Academic Research Software Engineer] to a postdoctoral-level position. The
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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and present the results at national and international conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a
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collaborative research environment. Education, Qualifications and Experience We are looking for outstanding candidates with a PhD in physics, electrical engineering, applied mathematics, computer science, or a
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models