PhD Graduate - Neural and Cognitive Engineering Researcher

2026 PhD Graduate - Neural and Cognitive Engineering Researcher

Join to apply for the 2026 PhD Graduate - Neural and Cognitive Engineering Researcher role at Johns Hopkins Applied Physics Laboratory.

Base pay range: $/yr - $/yr. Applications are accepted on a rolling basis.

Are you passionate about designing systems or algorithms using what we know about the mind and brain? Do you want to help invent the future of how people interact with intelligent systems? If you are graduating with a PhD in Biomedical Engineering, Neuroscience, Cognitive Science, Computer Science, or a related subject area, we would love to have you join our team!

We are seeking a researcher to contribute to and lead pioneering work in connectomics, neural interfaces, neurally-inspired artificial intelligence, and/or neurobehavioral research. We are a large multidisciplinary team of engineers and scientists engaged in groundbreaking research in applied neuroscience, artificial intelligence, robotics, and complex systems. We are looking for a motivated and collaborative teammate to support research and development of intelligent systems as a strategic advantage for the nation.

• Develop algorithms and/or systems in domains spanning connectomics, neural interfaces, neurally-inspired artificial intelligence, and/or neurobehavioral research.
• Collaborate with engineers and scientists to design and perform human subjects research, machine learning, software development, and/or biomedical signal processing.
• Communicate key findings internally across teams and externally to sponsors, including proposal development.

• Have a PhD in Biomedical Engineering, Neuroscience, Cognitive Science, Computer Science, or a related discipline.
• Have classroom or professional experience developing software and/or data analysis scripts.
• Have classroom or professional experience conducting research on connectomics, neural interfaces, neurally-inspired artificial intelligence, and/or neurobehavioral research.
• Be able to obtain a final Secret level security clearance (U.S. citizenship required). Eligibility requirements include meeting the requirements for access to classified information.

• Experience developing and/or implementing machine learning algorithms applied to biomedical data, including but not limited to neurophysiological data.
• Experience working on a fast‑paced government‑funded effort (e.g., DARPA project).
• Have a Secret level security clearance or above.

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. 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.

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.

This position is open to all qualified applicants, and we encourage individuals from diverse backgrounds to apply. APL is an equal opportunity employer in all aspects of employment and affirmative action.