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A position exists, for a Research Associate in the Department of Engineering, to work on probabilistic machine learning for the purpose of understanding and improving the performance of Large
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to explore and commercialize innovations at the intersection of AI systems and machine learning, with a goal to spin out a deep-tech startup. This is a unique opportunity for someone with both technical
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at the intersection of AI systems and machine learning, with a goal to spin out a deep-tech startup. This is a unique opportunity for someone with both technical expertise and startup ambitions to be part of a venture
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. We are now looking for: Three (3) Doctoral Researchers (PhD students) in Machine-Learning-Driven Atomistic Simulations The Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro
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predictive machine learning models for track and vehicle degradation using cutting-edge deep machine learning, and will integrate these into MoniRail's real-time monitoring system to deliver intelligent, data
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non-tumor signals with machine learning to find cancer in its earliest, most-treatable stages. Cancer is relentless. This is why Freenome is building the clinical, economic, and operational evidence to
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KTP Associate in Machine Learning ( Job Number: 25000811) Department of Computer Science Grade 7: - £39,105 - £43,878 per annum Fixed Term - Full Time Contract Duration: 30 months Contracted Hours
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Accountabilities Design and implement software pipelines to deploy ML models on edge devices with real-time inference capabilities. Optimize machine learning models (e.g., quantization, pruning) for edge hardware
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour