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2026 PhD Graduate - Robotic/Autonomous Systems Engineer - Maritime Robotics Group
2026 PhD Graduate - Robotic/Autonomous Systems Engineer - Maritime Robotics GroupThe Johns Hopkins University Applied Physics Laboratory • Laurel, MD, US
2026 PhD Graduate - Robotic / Autonomous Systems Engineer - Maritime Robotics Group

2026 PhD Graduate - Robotic / Autonomous Systems Engineer - Maritime Robotics Group

The Johns Hopkins University Applied Physics Laboratory • Laurel, MD, US
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Overview

Are you passionate about developing solutions to challenging problems in the field of robotics?

Do you love working in a collaborative environment with engineers of varied backgrounds and experiences?

If you are graduating with a PhD degree in Computer Science, Robotics, Mechanical Engineering, Electrical Engineering, or a related field and wish to work on some of the most challenging technical problems in robotics, we'd love to have you join our team! We are seeking engineers with educational experience and interest that aligns with the broad, exciting field of robotics. You will join a hardworking team of engineers in a collaborative development environment that spans software, hardware, and field testing. Our team works across a broad range of disciplines including machine perception, autonomous decision-making, data fusion, control systems, and mechanical design with applications across Uncrewed Air, Sea Surface, and Underwater vehicles. We are passionate about creating novel robotic solutions for our nation\'s Navy as well as committed to developing exceptional engineering talent and fostering a culture of innovation and collaboration.

As a member of our team..

Responsibilities

  • Your primary responsibilty will be to prototype next-generation robotic solutions to help address critical challenges facing our Navy.
  • You will work on highly collaborative, multidisciplinary teams to solve problems that span both software and hardware.
  • You will be part of an outstanding, dedicated team of engineers with deep experience in rapidly prototyping solutions from conception through field testing.

Qualifications

You meet our minimum qualifications for the job if you...

  • Have a PhD in Computer Science, Robotics, Mechanical Engineering, Electrical Engineering, or a related field.
  • Are skilled in software or mechanical design methodologies and techniques that can be applied to robotic systems
  • Have a passion for learning and a willingness to pick up and apply new skills.
  • Have the ability to work and collaborate effectively in a team environment.
  • Have a minimum 3.0 GPA on a 4.0 scale. Note : When prompted to upload attachments, please include a copy of your college transcripts (unofficial transcripts are acceptable).
  • Are able to obtain a Interim Secret security clearance to start and a final Secret Clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
  • You'll go above and beyond our minimum requirements if you...

  • Have research, classroom, or professional experience working closely with robotic systems, autonomous systems, or machine perception (including machine learning) algorithms.
  • Have experience developing in a modern, collaborative software or hardware development environment.
  • Possess a current active Secret clearance.
  • About Us

    Why Work at APL?

    The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation\'s most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

    At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work / life balance. APL\'s campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at http : / / www.jhuapl.edu / careers.

    All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accommodations@jhuapl.edu.

    The referenced pay range is based on JHU APL\'s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education / training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and / or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.

    Pay range

    Minimum Rate : $102,500 Annually

    Maximum Rate : $227,500 Annually

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