Radar Systems R&D Engineer: Signal Processing & ML

Penn State University; State College (Centre County); On-site; USD 90,000 - 130,000; Full time

Job summary

Penn State University’s Applied Research Laboratory (ARL) in State College, PA, seeks Systems Research and Development Engineers to advance radar signal processing and machine learning within the Materials Science and Applications Department. On-site work with periodic travel to remote locations is required.

You will design, implement, and transition algorithms for radar data on neuromorphic hardware, collaborating with senior engineers, scientists, and sponsors to deliver data products and

Qualifications

• Past success in data analytics/manipulation.
• Solid foundation in statistical signal processing (spectral analysis, filtering, detection and estimation).
• Proficiency in Python or C++.
• Ability to work independently and in a multidisciplinary team.
• Strong written, oral, and interpersonal communication skills.

Responsibilities

• Develop signal processing algorithms - Design, implement, and validate algorithms for deployment on neuromorphic chips.
• Collaborate with engineers, scientists, and military personnel to define problems and integrate expertise.
• Research new approaches and evaluate techniques for difficult signal processing problems.
• Execute analyses to assess algorithm performance with radar and simulated data.
• Deliver results and transition findings to sponsors and stakeholders.

Skills

Data analytics

Signal processing

Python

C++

Team collaboration

Communication

Education

Bachelor's degree

Tools

Git

Jira

Job description

Penn State University’s Applied Research Laboratory (ARL) in State College, PA, seeks Systems Research and Development Engineers to advance radar signal processing and machine learning within the Materials Science and Applications Department. On-site work with periodic travel to remote locations is required.

You will design, implement, and transition algorithms for radar data on neuromorphic hardware, collaborating with senior engineers, scientists, and sponsors to deliver data products and