Über diese Part Time - Student (Graduate) - AI Research Assistant Stelle bei Penn State University
APPLICATION INSTRUCTIONS:
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CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.
Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.
JOB DESCRIPTION AND POSITION REQUIREMENTS
The Graduate Research Assistant will assist with research, data analysis, process improvement, and AI exploration activities that support the development of a more efficient and stable academic scheduling process.
Job Duties
Responsibilities may include:
- Collecting, organizing, and analyzing historical scheduling, enrollment, classroom utilization, and related institutional data using Microsoft Excel and other analytical tools.
- Conducting literature reviews and environmental scans on AI applications, higher education scheduling systems, process automation, and scheduling optimization.
- Assisting in the evaluation of AI-enabled technologies (e.g., Microsoft Copilot, Power Automate, Ad Astra, Infosilem, UiPath, and similar platforms) for their potential application to academic scheduling.
- Documenting current scheduling workflows and helping identify opportunities for automation, standardization, and process improvement.
- Assisting with data reconciliation, validation, and preparation of scheduling datasets for analysis.
- Supporting the development of reports, presentations, process documentation, and grant deliverables for project stakeholders.
- Participating in project meetings and collaborating with faculty, administrators, and campus partners throughout the duration of the project.
- Performing other research and administrative tasks as assigned in support of the grant objectives.
Requirements and Qualifications
Selected applicants must be enrolled as graduate students at Penn State. Preference will be given to students with backgrounds or demonstrated interest in business analytics, information systems, computer science, engineering, artificial intelligence, operations management, data analytics, or related fields.
Preferred qualifications include:
- Strong analytical and problem-solving skills.
- Proficiency with Microsoft Excel and Microsoft Office applications.
- Experience working with data, databases, or process mapping.
- Familiarity with AI tools, automation technologies, or programming languages (e.g., Python, SQL, Power Automate, Copilot) is desirable but not required.
- Strong written and verbal communication skills.
- Ability to work independently while collaborating effectively as part of a multidisciplinary project team.
Compensation: $15.00 per hour.
BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.
CAMPUS SECURITY CRIME STATISTICS
Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.
EEO IS THE LAW
Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.
