Part-Time Systems Research and Development Engineer

Penn State University•University Park, IL

10d•Onsite

About The Position

Penn State’s Applied Research Laboratory (ARL), Materials Science and Applications Department (MSAD), seeks motivated and experienced Systems Research and Development Engineers. MSAD works on multidisciplinary topics, including signal processing, machine learning, and software design, with a focus on radar systems. The department applies advanced computing techniques to radar-based signals for training, rendering, and processing, producing data products and tools that support 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 encourages transitioning service members to apply through its DoD SkillBridge partnership. Higher-level responsibilities may include independently handling moderately complex assignments, leading defined project tasks or technical areas, developing and presenting new techniques to sponsors, guiding and reviewing junior engineers, tracking task budgets and funding, and contributing technical content to proposals and publications. Candidates must be U.S. citizens and eligible to obtain a government security clearance. Employment also requires successful completion of background checks and participation in ARL’s drug testing program, as well as compliance with applicable electronic and physical monitoring requirements.

Requirements

Past success working with data analytics and manipulation.
A solid foundation in statistical signal processing, including spectral analysis, filtering, and detection and estimation theory.
Programming ability in Python or C++.
Ability to work independently and collaboratively in a multidisciplinary team.
Strong written, oral, interpersonal communication, and presentation skills.
U.S. citizenship.
Eligibility to obtain a government security clearance; employment may require a government background investigation to establish or upgrade clearance eligibility.
Successful completion of University background checks.
Ability to participate in ARL’s drug testing program and 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 how to apply them to radar-based datasets.
Knowledge of Synthetic Aperture Radar and how its data can be used for analysis.
Experience manipulating data with higher-level programming 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.

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.
Research and evaluate new techniques for difficult or novel signal processing problems.
Analyze algorithm performance, data quality, and the feasibility of novel approaches using radar and simulated data.
Assess the behavior of currently deployed systems and develop capabilities to enhance them.
Communicate findings to stakeholders, scientists, and software engineers within ARL and at external sponsors.
Contribute to technical memos, reports, white papers, and study plans.
For higher-level positions, independently work on moderately complex assignments, review progress, and evaluate results.
For higher-level positions, lead defined tasks or technical areas within larger projects and present new techniques and analysis approaches to sponsors.
For higher-level positions, train and provide technical guidance to junior engineers and review their work.
For higher-level positions, monitor and track task budgets and funding.
For higher-level positions, contribute technical content to proposals and publications.