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breadth and critical thinking is particularly valuable. Prior coding experience in Python or R, with willingness to learn Python-based tools. Demonstrated experience in community engagement and wide
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
toxicology, pharmacokinetics, transport modelling, and/or gene-environment interaction studies would be beneficial but not required. Prior training and experience with R or Python, manuscript and grant writing
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Proficiency in Python and experience with PyTorch, TensorFlow, or JAX Demonstrated ability to complete technical projects (thesis, publication, or GitHub repo) Familiarity with clinical data is helpful but not
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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; semiconductor device fabrication; high frequency, low-noise electrical measurements; interfacing computers with instrumentation using LABVIEW; and programming in MATLAB, PYTHON, C++, and/or IGOR. For more
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related field Strong background in numerical methods and machine learning Proficiency in at least one programming language (Python, Julia, C++, …) Good analytical skills Good organizational skills and
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for this position is $60,000-$80,000 per annum + benefits. Postdoctoral Research Fellowship Translational Radiation Oncology The Analytics in Medical Sciences (AiMS) Institute https://aims.ok.ubc.ca
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(ES) - Conocimientos avanzados de mecánica cuántica, concretamente, información cuántica y redes cuánticas. - Experiencia en lenguajes de programación como Python o C. - Experiencia en el uso de
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on the NCN website: https://projekty.ncn.gov.pl/opisy/620203-en.pdf The project is interdisciplinary, combining field studies, environmental observations, laboratory analyses, and computational data-processing