Part-Time Research Assistant/Programmer - Yanxi Liu

APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.

• 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 Department of Computer Science and Engineering is seeking part-time Research Assistant/Programmer to assist with robotics and machine learning research as well as data collection and data analysis. This project is led by Dr. Yanxi Liu in the School of EECS at Penn State.  This position is a unique opportunity to contribute to cutting-edge research.

Position Details

• Anticipated Start Date: 6/30/25
• End Date: TBD
• Weekly Hours: 20 +/- hours per week (flexible scheduling)
• Compensation: $21 per hour

The following are foundational and necessary skills:

Programming & Environment:

• Python 
• Proficient in scripting, data manipulation, and debugging
• NumPy 
• Experience with array operations, broadcasting, and vectorization
• Linux / Unix 
• Familiarity with shell commands, SSH, file structures, and scripting
• Git 
• Version control using GitHub or GitLab

Mathematics & Geometry:

• Linear Algebra

• Basic matrix operations

• Coordinate Systems 

• Understanding of world, camera, and image spaces
• 3D Transformations
• Rotation, translation, scaling, etc., homogeneous coordinates

Deep Learning:

• Experience with at least one deep learning framework such as PyTorch or TensorFlow
• Understanding of:
  • Neural network architecture (e.g., CNNs)
  • Loss functions, optimization, and backpropagation
  • Training, evaluation, and debugging
  • Computer Graphics & Vision Fundamentals
  • Computer graphics basics 
  • Mesh structure (vertices, faces, normals)
  • Coordinate transformations 
  • Local vs. global frames, extrinsics/intrinsics

Application Instructions

To apply, please submit a resume and a cover letter detailing your background, relevant experience, and interest in this project, in WorkDay.

For inquiries, you may contact Dr.Yanxi Liu at yul11@psu.edu or Dr. Robert Collins at rtc12@psu.edu. We look forward to your application and the prospect of working together!

 

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.

 

The Pennsylvania State University is committed to and accountable for advancing equity, respect, and belonging in all its forms. We embrace individual uniqueness, as well as a culture of belonging that supports both broad and specific 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.

 

Federal Contractors Labor Law Poster

PA State Labor Law Poster

Penn State Policies

Copyright Information

Hotlines