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, or livestock waste systems. Experience with data analysis, modeling (e. g., ammonia emissions or air quality models), and statistical software (R, SAS, Python, etc.). Demonstrated ability to conduct independent
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. Programming experience (Python, MATLAB, Julia, or similar). Preferred Qualifications Experience with time-lapse electrical resistivity tomography (ERT) inversion techniques. Experience in hydrogeophysics
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in general. You are very well-versed working with data, models, statistics, simulations, and in general quantitative methods. Basic experience with programming (e.g. python) is a requirement, while
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; geometric or topological deep learning; higher-order network science; graph machine learning; or statistical physics of complex systems. Strong programming skills in Python and experience with modern
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, such as Python or Fortran. Experiences with machine learning is a plus to the application. Solid understanding of the physical hydrologic cycle and large-scale geographic datasets. The Pennsylvania State
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computational analysis of molecular and cellular biology data. Expertise in Python and/or R. A demonstrated ability to conduct independent research as demonstrated through a strong track-record of peer-reviewed
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. Expertise in Python is expected. A demonstrated ability to conduct research and produce scholarly outputs, as evidenced by publications in peer-reviewed journals. Familiarity with molecular and cellular
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clear orientation toward transdisciplinary collaboration. Proficiency in one or more relevant programming languages (e.g. R, Python, NCL, Julia, Fortran) and evidence of effective scholarly communication
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should have experience developing, implementing, or applying computational methods to large-scale biological datasets. Expertise in Python and/or R is expected. Experience with biological data processing
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computational analysis of proteomics data is highly desirable. Experience with Python, R, or related scientific computing tools; proteomics software platforms; biological databases; data repositories