Sobre este puesto de Research Assistant Positions - LLMs and AI for Data Analysis (Spring 2027) en Penn State University
APPLICATION INSTRUCTIONS:
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JOB DESCRIPTION AND POSITION REQUIREMENTS
The Department of Statistics at Penn State seeks to hire master's students in Computer Science or related fields as part-time Research Assistants for Spring 2027. Exceptionally qualified undergraduate students will also be considered.
Successful candidates will work on research projects involving large language models (LLMs), AI agents, and their applications in data analysis and scientific research. Responsibilities may include developing and evaluating LLM-based methods, implementing computational experiments, building research software, and analyzing experimental results.
Preferred qualifications include:
- Strong Python programming skills and demonstrated experience developing software or computational projects;
- Experience with machine learning, deep learning, or LLM applications, including model evaluation, fine-tuning, or agent-based systems;·
- Familiarity with relevant libraries and frameworks (e.g., PyTorch, Hugging Face Transformers, LangChain, or similar tools);·
- Experience with research projects, software development internships, or independent technical projects;·
- Ability to work independently, troubleshoot technical problems, and write well-documented, reproducible code.
Prior research experience is desirable but not required. Candidates with strong technical skills and an interest in conducting research are encouraged to apply.
Hours, wages, and anticipated periods of employment will vary based on project needs and applicant availability. In addition to the application on workday, please fill out this form RA application 2027 – Fill out form. Applications will be reviewed on a rolling basis. For full consideration, please apply by Nov. 20, 2026.
BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.
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EEO IS THE LAW
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