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other multi-omics datasets to identify biomarkers and mechanisms of therapeutic response. Develop computational workflows for spatial biology and imaging data analysis using R, Python, or related tools
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Required Working knowledge of at least one programming language, such as C++, Python, etc.; Working knowledge of Dynamic Traffic Assignment (DTA) and large-scale network simulation Have a good understanding
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, epidemiology or computer engineering discipline Strong software skills in at least one of the following: SAS (including macros and SQL), R, Python Experience managing large databases (preferably healthcare data
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human omics (preferably related to neurodegeneration) studies is expected. Solid skills in at least one programming language (R, Python or Perl) and experience working in Linux and/or high-performance
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experience in statistical genetics or genomics research, demonstrated through a peer-reviewed publication record, and excellent programming skills (Python, R, Linux, GitHub). Experience wrangling and analysing
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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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, 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