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recording. The work will also include developing new statistical data analysis tools for behavioral and neural data. More broadly, the postdoc will be part of a large and intellectually vibrant community
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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LanguagesENGLISHLevelExcellent Research FieldMedical sciences » MedicineYears of Research ExperienceNone Additional Information Benefits We offer a 4-year PhD position with market conform wages in a large, multidisciplinary
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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documentation. Ability to read, interpret, and carefully follow experimental protocols. Basic computer skills (Excel, Word, PowerPoint) with willingness to learn advanced software related to specific research
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: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Design nucleic-acid nanostructures and assemble them in a wet laboratory
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optoelectronic devices) while also connecting to application-driven areas of Electrical Engineering, such as Power and Cyber-Physical Systems, Machine Learning, and Intelligent Energy Systems. We particularly
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
. Basic knowledge of statistics and machine-learning Basic programming skills in R and/or Python Basic knowledge of mixed effects models Preferred Qualifications Master's degree in Data Science (or related
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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. ESSENTIAL REQUIREMENTS A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas. Documented expertise in: Machine/Deep Learning, and possibly Computer