123 coding-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Pennsylvania State University
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research offices and external sponsors Ensure compliance of all projects with Labor and Industry codes, Penn State Environmental Health & Safety policies, federal procurement guidelines, township and borough
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of Transportation testing for alcohol and controlled substances (49 CFR PART 40), and physical examination requirements as per PA. CODE 231.85. Penn State does not sponsor or take over sponsorship of a staff
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-quality code efficiently Work with engineers and scientists to implement algorithms, models, and data processing pipelines Apply engineering fundamentals to solve technical problems and contribute to system
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stakeholders, articulate architectural decisions and tradeoffs, discuss code and data flows in depth, and demonstrate a strong understanding of software quality. Responsibilities: Develop, test, and deploy high
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Dr. Meg Bruening. Part-time research assistants will assist with coding interviews, collecting community-based data including but not limited to surveys, interviews, and plate waste data in schools
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protocol improvements or revisions Collect, enter, code, and analyze data; contribute to the design of data plan; present study findings to research teams Develop and design project materials including
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for frequent, trouble-free deployments of infrastructure code, and deploy/operate workloads in container orchestration environments across bare metal and cloud Assist in performing and reviewing pull requests
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& Editing: Draft, review, edit, and format manuscripts for submission to peer-reviewed academic journals. Qualitative Analysis: Conduct qualitative data analysis, including coding, thematic analysis, and
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. Identify and mitigate risks associated with design, construction, safety, environmental health, code compliance, and schedule impacts; develop contingency plans as needed. Ensure compliance with applicable
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-organized code for data processing and analysis workflows Ideal candidates will have an M.S. degree (or higher) and prior experience with Python, tropical cyclone datasets, statistical-dynamical TC