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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA
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, that will work halftime with the NU Public Evaluation Lab (NU-PEL) on the evaluation of the Boston Area Youth Direct Cash Transfer (BAY-CASH) program and half-time with Dr. Jonathan Zaff on a research
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., epidemiology, applied mathematics, statistics, or network science) by the start of the appointment, Experience developing complex models for real world data, with strong programming skills (R, Python, and/or
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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA
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in worldwide experiential learning, urban engagement, and interdisciplinary research that meets global and societal needs. Our broad mix of experience-based education programs?our signature cooperative
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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA
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engagement, and interdisciplinary research that meets global and societal needs. Our broad mix of experience-based education programs?our signature cooperative education program, as well as student research
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postdoctoral researcher to take a leading role in a research program that explores the interactions between wood-eating teredinid bivalves (commonly known as shipworms) and their intracellular bacterial
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functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
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: Demonstrates the ability to plan and execute research. Excellent verbal, and written communication skills, attention to details, as well as training in research methodology and quantitative data analysis