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medicine. · Analyze and interpret complex multiomics datasets, including bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics data using R, Python, and advanced
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Classification Title: Post-Doctoral Associate in unsupervised and generative ML for chemistry Classification Minimum Requirements: PhD in Chemistry or related area Strong coding (Python) and
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; machine learning or deep learning; pharmacogenomics; computational biology; drug discovery; network medicine; NLP/large language models; or precision medicine 2. Strong programming skills in Python, R
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serving as a trusted advisor to executive-level data leaders and government practitioners. Knowledge of common data analytics tools (e.g., SQL, Python, Tableau), cloud data infrastructure, and data
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driven analysis of redistricting plans for all 50 states combining census data, precinct-level results, and other information using Python (including numpy) and GIS software. Publish codebooks and datasets
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). Familiarity with one programming language, particularly Python, is desirable but not required. An interest and willingness to learn new methods. A willingness to self-initiate troubleshooting of technical
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driven analysis of redistricting plans for all 50 states combining census data, precinct-level results, and other information using Python (including numpy) and GIS software. Publish codebooks and datasets
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courses of responsibility are introductory computer programming with Python and mechanics and/or electricity and magnetism engineering physics. Strong written and verbal communication skills are required
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related field. Familiarity with scripting languages such as Python or systems engineering is a plus. Self-motivated, strong organizational skills and attention to detail with strong verbal and written
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Current student in computer science, data science, information systems, engineering, or a related field. Working knowledge of Python programming. Experience working with REST APIs and JSON data