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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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. The project sits at the intersection of machine learning, neuroscience, and behavior, with applications ranging from music cognition to speech-in-noise perception in audiology. You will work with naturalistic
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position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse scientific and security problems
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Reporting to the PI, Prof Erin Saupe, the post holder will be a member of a research group with responsibility for carrying out research for ERC grant ‘Determining the drivers of extinction across space and time’. The post holder will provide guidance to less experienced members of the research...
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing
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We are seeking two full-time Postdoctoral Research Assistants in Machine Learning to join the Foerster Lab for AI Research group at the Department of Engineering Science (central Oxford). The post
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Details Title Postdoctoral Fellowships in Networking Support for Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning to provide leap-ahead mission
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Senior Machine Learning Engineer (Full‑Stack / Applied‑Research) – Mission Innovation Lab At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions
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properties. Our group uses theoretical and computational chemistry, physics, and materials science in combination with chemical machine learning to explore and exploit diverse functional organic and hybrid