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populations). Proficiency in R, Python, and SQL. Certifications/Licenses Required Knowledge, Skills, and Abilities Leadership role on funded grant(s). Preferred Qualifications Experience with EHR data such as
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Biophysical and Biomedical Measurement Group, National Institute of Standards and Technology | Gaithersburg, Maryland | United States | 2 months ago
measurement workflows. - Strong data-analysis skills using Python, MATLAB, Mathematica, Origin, R, or similar tools. - Strong written and oral communication skills. Highly desired: - Experience designing and
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, GraphPad Prism, Python/R, or related tools. Experience or interest in cancer pharmacology, immuno-oncology, natural killer cell biology, drug discovery and development, translational therapeutics, blood
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analytical research on cell-type specific human brain development, and neurological diseases. The project will involve bioinformatic analyses of large datasets with Python and R programming languages. It is
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for advanced data analysis and/or experimental control (e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in
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the Linux operating system, bash scripting, Git, Python, and reproducible software environments. Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep
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technologies Proficiency in using Excel, Python, R or similar tools for engineering data analysis is preferrable Excellent written and oral communication skills Motivated self-starter with the ability to work
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samples and myeloma cell lines. Preferred: experience with NGS analysis, R/Python, other computational languages, bioinformatic analysis. References: Mikulasova A, Morgan GJ, Walker BA (2022) Chromosomal
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Sub-Saharan Africa and conducting epidemiological research on pediatric cancer disparities for patients treated in the US. The Postdoctoral Associate will use R or Python to maintain data pipelines
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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C