R&D Engineer Intern

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 Geospatial, Imaging, and Data Sciences Division (GIDS) of the Applied Research Laboratory is seeking undergraduate students for internship opportunities. ARL’s purpose is to research and develop innovative solutions to challenging scientific, engineering, and technology problems in support of the Navy, the Department of Defense (DoD), and the Intel Community (IC).

Typical duties include research and development in areas such as defense, law enforcement, security, disaster relief, human geography, disaster preparedness, and first response. Our team is interested in both undergraduate-level and graduate level student interns.

ARL is an authorized DoD SkillBridge partner and welcomes all transitioning military members to apply.

You will:

• Collaborate with geospatial data analysts to understand and automate workflows and improve human processes to advance the discovery and modeling of associations, trends, patterns and system dynamics
• Create processes and algorithms to transform traditional GEOINT and open-source data into spatial-temporal information describing places, events, and activities
• Combine full spectrum source data with modeling capabilities that associate real world objects to known signatures and doctrines
• Develop the ability to discover and capture information from geospatial data to better represent the most advanced understanding of world events, systems, and discrete entities
• Apply the scientific method across multiple disciplines to advance Data and Geospatial Sciences and develop data analytics through systematic experimentation
• Conduct experiment-driven applied research and development
• Conduct analysis and complete scientific research projects and develop geospatial algorithms while collaborating among diverse domains to further scientific understanding and analytic tools
• Grow career and capabilities, plan and conduct applied research, provide technical guidance and oversight, contribute to large research efforts, report results, foster trusted relationships with sponsors, and advise on new and evolving technology and techniques
• Research team members will receive technical and professional mentorship to learn about conducting efficient experiment-driven applied research investigations on diverse multi-disciplinary teams
• Engage in research efforts ranging from proof-of-concept through integrated production systems

Students studying Mathematics, Engineering, or Computer Science are encouraged to apply.

Required skills/experience areas include:

• Python, R, Java, C++, or Matlab
• Previous success with collaborations in a diverse, multi-disciplinary, team-oriented culture
• Relevant experience or coursework in a field directly applicable or highly related to Data Sciences, Engineering, Computer Sciences, or Geospatial Sciences
• Ability to design experiments, perform analysis, and design or apply meaningful metrics to measure results
• Demonstrated ability to adapt and learn new skills, execute specific research projects, and meet task deadlines and goals
• Strong ability to clearly communicate ideas and information to ensure mutual understanding

Preferred skills/experience areas include:

• Ability to utilize Git for distributed version control and team collaboration
• GUI development
• Open-source scientific computation
• Computer vision
• Modeling
• Machine learning tools

The successful candidate will work up to 20 hours/week during the fall and spring semesters and 40 hours/week over the summer.

This is a paid internship located at ARL's Main Lab Building at the University Park Campus; relocation and housing are not provided.

ARL’s purpose is to research and develop innovative solutions to challenging scientific, engineering, and technology problems in support of the Navy, the Department of Defense (DoD), and the Intel Community (IC). 

FOR FURTHER INFORMATION on ARL, please visit our web site at www.arl.psu.edu.

BACKGROUND CHECKS/CLEARANCES

Employment with the University will require successful completion of background check(s) in accordance with University policies.All positions at ARL require candidates to possess the ability to obtain a government security clearance; you will be notified during the interview process if this position is subject to a government background investigation.  You must be a U.S. citizen to apply.  Employment with the ARL will require successful completion of a pre-employment drug screen.

CAMPUS SECURITY CRIME STATISTICS

Federal Contractors Labor Law Poster

PA State Labor Law Poster

Penn State Policies

Copyright Information

Hotlines