Part Time - Student (Work-Study)(Undergraduate) - Artificial Intelligence & Image Processing Research Assistant

Penn State Yorkmid

Research AssociateLaboratory & Life Sciences

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Research AssociateLaboratory & Life Sciences

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This position requires you to have received a work-study award. To verify if you have received a work-study award, please consult the Financial Aid Award Summary area in your LionPATH account. A Federal Work Study award does not guarantee a job is available.

The Science Department at Penn State York is seeking a motivated undergraduate student majoring in a science or engineering program to join our research team for the 2026-2027 Academic Year. As an Undergraduate Research Assistant, you will collaborate with the principal investigator and fellow team members on research projects focusing on convolutional neural networks (CNNs) for image processing applications. This position offers an opportunity to gain practical coding experience and contribute to cutting-edge artificial intelligence projects. Students may work up to 15 hours per week.

Currently enrolled as an undergraduate student in an engineering or science program at Penn State York with an eligible Work-Study award.
Strong attention to detail and the ability to follow strict coding and data protocols.
Eagerness to learn and contribute meaningfully to ongoing research initiatives.
Excellent teamwork and interpersonal communication skills.
Familiarity with programming using MATLAB and Python.

The starting hourly rate for this job is $15.00.

Federal Work Study job performance is evaluated either annually or through ongoing mentorship. Students who received a Federal Work Study award have the opportunity to obtain a job and perform related duties either on campus, or remotely, if possible and at the discretion of the employer. Students applying for Federal Work Study positions should clarify expectations with their potential employer regarding either on campus/in person or remote work arrangements.

Data Simulation: Assist in generating and simulating datasets using computational tools and programming environments.
Data Management: Collect experimental data from open-source repositories and store them according to established laboratory protocols for future research use.
Data Analysis: Process and analyze experimental data, visualize trends, interpret results, and draw meaningful conclusions.
Algorithm Implementation: Employ convolutional neural networks to enhance image processing capabilities and develop innovative solutions for challenges in various scientific, engineering, and medical applications.
Report Compilation: Collaborate with team members to compile research findings into comprehensive formal reports.
Professional Communication: Develop effective communication skills by presenting research outcomes and actively contributing to project discussions.

Employment with the University will require successful completion of background check(s) in accordance with University policies.

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.

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.

Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university’s teaching, research, and service mission.

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