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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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engineering pipelines. Implement models in Python using frameworks such as PyTorch, TensorFlow. Perform statistical analyses and model benchmarking against existing methods. Collaborate with wet-lab scientists
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presentations using Power Point, R/Python and other graphics software as needed. Search literature for references to technical problems and keep informed by reading technical journal and publications. Present
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relevant field Proficiency in Python, and/or R statistical package. Proficiency in using LLM, model training, and Generative AI. Experience with supervised and unsupervised ML techniques Skill in collecting
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the oceanographic community including MatLab, Ferret, and/or Python. ● The incumbent must have a proven publication record, strong scientific writing and computer skills, and the ability to communicate science to
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, Statistics, Genetics, Computer Science, or a related field. Excellent communications skills in English (both verbal and written). Proficiency in using R/Bioconductor and Perl/Python for genomic data analysis
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learning methods Strong programming skills in Python and/or R Experience with deep learning frameworks (PyTorch or TensorFlow) Knowledge, Skills and Attitudes: Snakemake pipeline development with Conda
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, checking, recoding data for analysis). At least intermediate knowledge of SAS or R programming required. Knowledge of Python and/or machine learning helpful but not required. The University of Miami offers
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cytometry. • Must have experience working with vertebrate animal models. • Experience with CRISPR and shRNA technology preferred. • Experience with R or Python and ability to analyze large datasets
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evaluations, including experience with quality assessment tools for economic studies. Programming skills for reproducible research workflows (e.g., GitHub version control, R Markdown, Python for data processing