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Electrical Engineering, Computer Engineering, or Computer Science 2. Demonstrated, successful experience programming in algorithm level languages such as Matlab/Simulink, Python or similar . 3. Demonstrated
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides
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areas of nanoscience and nanotechnology. Job Title: Research Support Technician in Active learning Research area or group: Theoretical and Computational Nanoscience Description of Group/Project: In
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Machine Learning Scientist to join the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including
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, coordination, and management of information and data, development and implementation of computer models and simulations, development of research materials (figures, presentations, papers, etc.) and work
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computational tools and algorithms developed in the lab for processing and visualizing proteomics data (known as FragPipe computational platform). The individual will work in close collaboration with other
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and implements dynamic models, including machine learning algorithms, to optimize student-centered outcomes. Creates clear and actionable visualizations and dashboards using tools such as Power BI
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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are seeking highly motivated Research and Development Engineers to join our Computational Intelligence and Visualization Application Department of the Applied Research Laboratory (ARL) at Penn State. You will