Part-Time Systems Research and Development Engineer

The Pennsylvania State University•University Park, FL

9d•Onsite

About The Position

Penn State’s Applied Research Laboratory (ARL), within the Materials Science and Applications Department (MSAD), seeks motivated and experienced Systems Research and Development Engineers to work on multidisciplinary problems focused on radar systems. MSAD applies computing techniques to radar-based signals, including training, rendering, and processing, to generate data products and tools supporting military sponsors and national defense. The engineer will work closely with senior subject matter experts to develop, analyze, and transition signal-processing algorithms, while contributing technical expertise and expanding knowledge of national defense systems. The role is fully on-site in State College, Pennsylvania, and requires periodic travel to remote locations. ARL is an authorized DoD SkillBridge partner and encourages transitioning service members to apply. Additional responsibilities for higher-level positions include independently handling moderately complex assignments; leading defined tasks or technical areas; developing new techniques and analysis approaches; presenting results to sponsors; training and guiding junior engineers and reviewing their work; tracking task budgets and funding; and contributing technical content to proposals and publications. Applicants must be U.S. citizens and eligible to obtain a government security clearance. Employment requires successful completion of background checks. Employees must participate in ARL’s drug-testing program and comply with applicable electronic and physical monitoring requirements. ARL operates in a secure information environment, and personal electronic devices brought onsite must be registered and may be restricted in certain areas.

Requirements

Past success working with data analytics or data manipulation.
A solid foundation in statistical signal processing, including spectral analysis, filtering, and detection and estimation theory.
Proficiency with Python or C++.
Ability to work independently and collaboratively in a multidisciplinary team.
Strong written, oral, interpersonal communication, and presentation skills.
Must be a U.S. citizen.
Must be eligible to obtain a government security clearance.
Must complete required background checks and participate in ARL’s drug-testing program.
Must comply with electronic and physical monitoring requirements applicable to federal contractors.

Nice To Haves

Bachelor’s degree in a relevant field.
Knowledge of basic machine-learning algorithms and their application to radar-based datasets.
Knowledge of Synthetic Aperture Radar and how its data can be leveraged for analysis.
Experience manipulating data using higher-level coding languages and their built-in packages.
Experience with version-control and project-tracking tools such as Git and Jira.
Current eligibility for access to classified information at the Top Secret level or higher; clearance eligibility may be subject to a government background investigation for upgrade if required.

Responsibilities

Develop, implement, and validate signal-processing algorithms for deployment on neuromorphic chips.
Collaborate with senior engineers, scientists, and military personnel to define problems, refine approaches, and integrate multidisciplinary expertise.
Investigate and evaluate new techniques for difficult or novel signal-processing problems.
Evaluate algorithm performance, data quality, and the feasibility of new approaches using radar and simulated data.
Understand the behavior of currently deployed systems and develop capabilities to enhance them.
Communicate findings to stakeholders, scientists, software engineers, and external sponsors.
Contribute to technical memos, reports, white papers, and study plans.
For higher-level positions, work independently on moderately complex assignments, review progress, and evaluate results.
For higher-level positions, lead defined tasks or technical areas within larger projects, develop analysis approaches, and present results to sponsors.
For higher-level positions, train and provide technical guidance to junior engineers and review their work.
For higher-level positions, monitor task budgets and funding.
For higher-level positions, contribute technical content to proposals and publications.
Travel periodically to remote locations.