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Qualifications* PhD in computational biology, bioinformatics, data science, or a related quantitative field. Proficiency in Python and/or R; experience with high-performance computing environments. Experience with
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for QMSS (including which course(s), if applicable) and the skills (e.g., analytical tools such as Excel, R, Tableau, Python, etc.) and experiences (e.g., jobs, internships, research, coursework, teaching
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completion of CSC 379 or other relevant course (Algorithm and Complexity Analysis) Desired Qualifications* Experience with Colab, Python and LLMs. Modes of Work Hybrid The work requirements allow both onsite
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/engineering or data science field. The ability to do serious data munging and data wrangling is important. Demonstrated experience with SQL plus knowledge of Python. Using these tools to merge large datasets
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and large language models on unstructured EHR text; applying transformer architectures adapted for biomedical applications; and using Python, SQL, PySpark, AWS cloud computing environment, Databricks
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/Aruba Wireless Networks, specifically large scale deployments of more than 10000 access points; Aruba controllers and AOS software; Aruba Clearpass; scripting using Python; designing and maintaining
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workflows Experience with programming languages such as R, Python, SAS, or Stata Experience with dashboarding and visualization tools (Tableau, Power BI) Prior experience supporting NIH, AHA, or other
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teaspoon languages, writing programs in the Snap! programming language (https://snap.berkeley.edu/ ), and learning to transfer their knowledge to industry standard notations like Python, Processing, and HTML
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common statistical software programs, such as: Stata, R, SAS, Python, etc. Ability to pass a federal background investigation to secure Special Sworn Status with the U.S. Census Bureau. Desired
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duties Desired Qualifications* Experience AMQP/STOMP messaging platforms (e.g., RabbitMQ) Experience with programming/scripting languages (e.g., Ruby, Python, and PHP) Experience using source code control