2027 Internship - Signal Processing, Sensing, Computer Science, Algorithm Development, AI-ML

Johns Hopkins Applied Physics Lab

Laurel (MD)

On-site

USD 31,000 - 66,000

Full time

2 days ago
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Job summary

Johns Hopkins University Applied Physics Laboratory (APL) invites self-motivated students to spend the summer with a team of engineers, physicists, mathematicians, and computer scientists who are experts in their field. You will develop large-scale simulations of electromagnetic fields and radar systems, and prototype novel signal processing techniques for potential deployment by the military.

You will also optimize algorithms on multi-million dollar clusters and apply data science and machine

Qualifications

  • GPA of 3.0 or higher on a 4.0 scale.
  • Pursue a degree in a STEM field such as Electrical Engineering, CS, Aerospace, CE, Systems, Mechanical, Engineering Physics, Applied Physics, or Applied Math.

Responsibilities

  • Develop large-scale simulations of electromagnetic fields and radar systems.
  • Optimize algorithms to run on multi-million dollar computing clusters.
  • Prototype novel signal processing techniques for potential deployment by the military.
  • Apply machine learning to complex datasets and sensing problems.
  • Demonstrate ability to obtain interim and ultimately secret security clearances.

Skills

Problem solving
Communication skills
Collaboration
Security clearance eligibility

Education

Bachelor’s/Master’s/PhD in a technical field

Job description

Description

Are you self-motivated and passionate about solving some of the most complex problems encountered in defending our nation? Spend the summer with our team of engineers, physicists, mathematicians, and computer scientists recognized as experts in their field and contribute to the next generation of sensor algorithms to eliminate our adversaries’ ability to evade detection.

  • Develop large scale simulations of electromagnetic fields and radar systems
  • Optimize algorithms to run on multi-million dollar computational clusters
  • Prototype novel signal processing algorithms to be deployed by our military
  • Use machine learning techniques to augment current and future capabilities
  • Gain an understanding of electromagnetic phenomena to see how they can be used and exploited
  • Apply data science and machine learning to complex, large scale datasets
Qualifications

You meet our minimum qualifications for a position on our team if you…

  • Are in a Bachelors, Masters, or PhD program in Electrical Engineering, Computer Science, Aerospace Engineering, Computer Engineering, Systems Engineering, Mechanical Engineering, Engineering Physics, Applied Physics, Applied Math or another related technical field
  • Have a minimum 3.0 GPA on a 4.0 scale
  • Have strong problem solving/analytical skills
  • Have excellent verbal, written and presentation communication skills
  • Can collaborate effectively with colleagues from varied subject areas and experience levels
  • Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level 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 previous internship or research experience in signal processing, sensing, computer science, algorithm development, or AI-ML
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 https://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 Accessibility@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.

Minimum Rate

$22.60 Hourly

Maximum Rate

$47.95 Hourly

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