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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
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, project management, and ability
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related field experience with numerical models and/or large observational datasets strong skills in scientific programming (e.g. Python, Fortran, or similar) ability to work independently and in
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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members and collaborators. For additional information about the Liao research group, please visit: https://sites.google.com/view/chentingliao/ Department Contact for Questions: Questions regarding
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validation of energy system solutions will be an advantage. Strong programming skills in Python, MATLAB or similar environments are required, and it will be advantage if you have worked with hardware-in
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: agrivoltaics, ecovoltaics, solar PV performance modeling, biophysical/crop modeling, or techno-economic assessment (TEA) Advanced proficiency in Python or a similar scientific programming language, with a focus
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considered a strong advantage. Proficiency in statistical programming languages such as Python, R, is expected, as is the ability to work with complex clinical datasets and handle missing data thoughtfully
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programming languages such as C/C++, MATLAB, or Python. A strong publication record is an advantage. What We Offer The appointment will commence as soon as possible on a temporary basis for 1 year, with
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learning and statistics. A good command of Python programming is essential, as is a good command of English, both spoken and written. Skills in optimal transport theory and knowledge of generative models
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(Python required; R, C++ appreciated). Strong interest in network modeling, multi-criteria optimization, or graph theory. Skills in statistics and data analysis. Experience in 3D modeling, phenotyping