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. The successful candidate will have knowledge in programming, preferably in Python, experience working in a Unix environment. They will be independent, motivated, and highly organized and will help the investigator
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their data needs and objectives. • Perform data analysis and generate reports as needed. • Stay current with data analysis tools and techniques, particularly in R, Python, and SAS. • Helping prepare materials
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, Computer Science, Computational Biology, Bioinformatics or a combination of related education and work experience to equal four years. - Experience in Python, Rust, R or other common programming languages (e.g., C/C
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skills in R programming - Working knowledge of Python - Experience with basic analyses to characterize gut microbiomes, including diversity analysis, differential abundance analysis, modeling microbial and
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data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include software development (mostly in R, or in Python/TensorFlow/Keras
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assist with rodent experiments as needed. Some nights and weekends may be required. A breakdown of time would include the following: Data science and programming (60%): Build analysis codes in Python
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degree -Prior course work in computer analytics and advanced mathematics -Programming experience preferred: SAS, R, STATA and Python -Eligibility for certification using restricted CDC data sets Preferred
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management (Matlab, MySQL) •May be trained to process neuroimaging data on the UMN MSI and CMRR servers: HCP and inhouse pipelines (e.g., ANACONDA, Python, FSL, AFNI, SPM, CONN) Managerial tasks, oversight and
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(Matlab, MySQL) •May be trained to process neuroimaging data on the UMN MSI and CMRR servers: HCP and inhouse pipelines (e.g., ANACONDA, Python, FSL, AFNI, SPM, CONN) Managerial tasks, oversight and
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on clinical text analysis. Annotate, clean, and preprocess clinical notes and other healthcare-related text using Python or NLP toolkits Assist in building, fine-tuning, and evaluating NLP models for tasks