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Field
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Preferred Qualifications: Experience with neurorehabilitation or motor recovery research Proficiency in programming and data analysis tools (e.g., MATLAB, Python, R, SPM, FSL) Familiarity with human subjects
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implement new computational and statistical methods. Create, test, and use relevant computer code (R, Python, SQL or equivalent). Maintain, modify, and execute analytic machinery that results. Draft
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, computer science, or a related field. Technical Skills: Proficiency in programming languages such as Python, R, and MATLAB. Experience with machine learning frameworks and bioinformatics tools. Research
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: C++, Python, Matlab, R. ● Building analytical pipelines that include image processing, image registration, auto-segmentation, feature extraction, pathomics, and radiomic analysis ● Proficiency
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essential. Prior experience in informatics/programming (Python, R) or omics data analysis is not required but a strong interest in developing these skills is highly desirable. Starting salary will follow NIH
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University of California, Los Angeles | Los Angeles, California | United States | about 10 hours ago
conducting data analyses using R, STATA, or SAS • Ability to effectively work with community organizations, including clinical settings • Strong interpersonal and written and verbal communication skills
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- dimensional data. Strong programming skills (e.g., in Python or R) for handling large datasets and implementing models. A genuine curiosity about how knowledge is produced, shared, and applied across different
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statistical software such as SAS, STATA, or R. Excellent verbal and written communication skills in English. Strong organizational abilities, creativity, attention to detail, enthusiasm for mentoring, and
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, deep learning, or statistical modeling. Demonstrated experience working with clinical, digital health, or related biomedical data. Proficiency in Python, R, or other scientific programming languages
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decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more efficient and reliable