111 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at California Institute of Technology
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Radio Frequency Interference (RFI) engineering specialist to work on the DSA-2000 project (https://www.deepsynoptic.org/ ), a world-leading telescope that is currently in the design phase. The array will
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. For more details, see: https://roman.ipac.caltech.edu Essential Job Duties As a scientist on the Roman Science Support Center team at IPAC, you will: Develop and test algorithms for extracting near-infrared
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-of-the-art algorithms for detecting and classifying safe landing zones using computer vision techniques in order to design and develop custom models for detecting landing zones in real-time based on drone
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research program in Artificial Intelligence (AI) and Mathematics. This position involves applying machine learning tools, particularly reinforcement learning (RL), to address complex research-level
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Qualifications Familiarity with automated liquid handling platforms, with a desire to acquire higher-level skills in this area. Computer literacy and basic programming skills, preferably VBA/VB.NET in the MS Excel
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research program in Artificial Intelligence and Mathematics. Working under the guidance of senior researchers, the individual will help apply machine learning methods, with a focus on reinforcement learning
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at the interface of machine learning, data science, and the chemical sciences to lead the AI for the Chemical Sciences Summer Bootcamp. This individual will design and deliver an intensive, hands-on educational
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of experience in Python and proficiency in PyTorch. Experience in signal processing and machine learning for biomedical applications. Preferred Qualifications Programming in C++. Required Documents Resume
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AI or machine learning tools applied to facilities analytics or scenario modeling. Experience with SQL, Python, or comparable data analysis tools. Professional certifications such as CFM, CEFP, IFMA
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. Essential Job Duties Responsible for the design, implementation, and testing of GPU computer kernels, and associated host code, for the CHR real-time pipeline. Will make recommendations on the requirements