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computing environments, and GPU programming. Necessary skills include knowledge of data processing using software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab
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modeling, including the building of neurobiological models with drug-relevant targets and clinically relevant outcomes. * Track record (GitHub) demonstrating proficiency in the Julia programming language
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong programming skills, including TensorFlow and/or
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-driven applications. Demonstrated expertise in designing, implementing, and evaluating complex software systems. Strong programming skills in relevant languages (e.g., Python, C++, Java) and experience
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. Excellent scientific writing ability and strong oral communication skills. The ability to work effectively and collegially with colleagues. Additional qualifications as specified by the Principal Investigator
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. Preferred Qualifications: Knowledge of computer models on watershed assessment and/or flood management. Knowledge of programming or scripting languages such as Python, Fortran, R, or others. Experience in
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an appropriate field. Excellent scientific writing ability and strong oral communication skills. The ability to work effectively and collegially with colleagues. Additional qualifications as specified by
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curious to deliver work that matters, your journey starts here! The Language Technologies Institute (LTI) at Carnegie Mellon University is a world-renowned research and education hub at the forefront
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computational fluid dynamics (CFD), cardiovascular modeling, or biomechanical growth and remodeling. Demonstrated experience with numerical methods (e.g., finite element method), programming languages (C
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal