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postdoctoral or more senior researcher interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling
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computer-related support while maintaining a high level of customer satisfaction. The successful candidate will maintain a presence at the PPPL Help Desk while enhancing skills such as IT system deployment
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Quality Assurance activities such as narcotic counts and safety checks. Monitors food services, janitorial services, equipment, and supplies. Appropriate use of current computer programs. Assumes
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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across the broad areas of Statistics and their applications in machine learning. The ORFE department is part of the School of Engineering and Applied Science which is pursuing several initiatives in
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) is required. Preferred Qualifications: Familiarity with machine learning methods for neural data analysis and strong programming skills. This position is subject to the University's background check
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biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant to genomics -bioinformatics -population genetics / genomics
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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. Fabricate parts as required using a variety of equipment and tools such as: milling machine, lathe, drill press, band saw, and other industrial tools. Assist in the set up and operation of pneumatic
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basic computer literacy and the ability to work with computerized maintenance management software (CMMS) to receive work orders and provide documentation. Is able to work proficiently with all types