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information that is processed through a machine learning element. The role will also require regular contributions to a variety of academic tasks, including positively interacting and communicating with
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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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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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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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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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. 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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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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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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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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School of Computing & Mathematical Sciences Location: Greenwich and Medway Campuses Salary: £38,249 to £44,128 Contract Type: Permanent Release Date: Friday 25 July 2025 Closing Date: Friday 08 August 2025 Interview Date: To be confirmed Reference: FES013-E We invite applications outlining...