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pipelines using Python and R, leveraging frameworks such as TensorFlow and PyTorch for imaging and omics-based applications. Applying state-of-the-art techniques in data science and AI to analyze the cellular
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knowledge sharing Expected Salary: $20/hr Required Qualifications: Proficient in Python programming; knowledge of R is a plus. Understanding of machine learning and deep learning concepts, with proficiency in
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analysis and data science methods, working with the NIH Project Officer. Position will utilize various statistical software packages, including Python, R, SAS, Jupyter Notebook, and SQL, to perform data
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studies. Develop and apply advanced statistical methods and machine learning techniques using tools such as R and Python. Integrate and run process-based models (e.g., crop models, hydrologic models
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to confidential data. Utilize software tools such as Excel, Tableau, and Python to aid in various projects. Adhere to university policies and federal/state privacy regulations. Regularly meet with the supervisor
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and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques. Preferred Qualifications: Prior working experience with EHR data, machine
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data analysis. Record of scholarly publications and scientific communication skills Proficiency in statistical and data analysis tools (e.g., MATLAB, Python, R). Preferred Qualifications: Experience with
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PostgreSQL Expertise in configuration management tools such as ansible, puppet, and chef Expertise in orchestration tools such as Terraform Expertise in scripting/programming languages such as Python and
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knowledge (R, Python, or other programming languages) or ability to learn. Excellent oral communication and written skills in English, with good organization, attention to detail, and analytical abilities
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in such a way as to be accessible by lay and professional audiences Technology • Using R, SAS, Python, SPSS, Tableau, and/or other database/analytical software platforms at an intermediate level of