784 machine-learning-"https:"-"https:"-"https:" positions at Pennsylvania State University
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systems, devices (including fabrication) and sensors, robotics and automation, artificial intelligence and machine learning, advanced electronics, and communications. Our faculty are particularly encouraged
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REQUIREMENTS The Department of Nutritional Sciences is seeking applicants for part-time job of learning assistants to help with NUTR 100 for academic year FA 2026/SP 2027. Job duties to include: answering emails
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to represent and interpret biological imaging data, enabling new scientific discoveries. Responsibilities include designing interpretable end-to-end machine learning frameworks to explain biomolecular condensate
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research project investigating self-supervised visual learning inspired by human perception. Responsibilities may include developing and evaluating machine learning and computer vision algorithms
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provides technical and administrative support for an interdisciplinary research project focused on computational behavioral neuroscience, computer vision, and machine learning analysis of rodent behavior
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for an engineer who enjoys building reliable, scalable systems for machine learning, data-intensive research, and advanced computing workloads. The successful candidate will work across GPU systems, HPC platforms
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who enjoys building reliable, scalable systems for machine learning, data-intensive research, and advanced computing workloads. The successful candidate will work across GPU systems, HPC platforms
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appointment. Job duties Mentoring new PhD students in numerical computational projects. Conducting comprehensive literature reviews in machine learning for subsurface flow and well performance and supporting
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Working experience in algorithm design and implementation in software (e.g. C/C++, MATLAB, python, etc.) Understanding of data analysis, statistics, probability, and machine learning applied to IQ signals
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Working experience in algorithm design and implementation in software (e.g. C/C++, MATLAB, python, etc.) Understanding of data analysis, statistics, probability, and machine learning applied to IQ signals