Computational Physicist – Physics- Scene and Signature Modeling

Description

Do you enjoy diving deeply into new technical fields, building subject matter expertise, and sharing that knowledge with others?

Are you passionate about using physics, mathematics, and computation to understand what sensing systems observe in complex real-world environments?

Would you like to develop physics-based modeling, simulation, and analysis capabilities for observable signatures, image formation, and remote sensing applications?

If so, we're looking for someone like you to join our team at APL.

We are seeking a creative, highly motivated computational physicist with a Ph.D. background in physics, applied physics, mechanical engineering, aerospace engineering, or a closely related technical field. As a member of our team, you will develop expertise across interdisciplinary areas and translate that expertise into physics-based models, simulations, and software tools. We value people who are intellectually curious, self-directed learners, eager to work across teams, and comfortable serving as a common technical reference point for collaborative development efforts.

• Develop subject matter expertise across multiple technical areas and use that knowledge to guide physics-based modeling and analysis efforts.
• Design, develop, test, and maintain computational tools for physics-based scene and signature modeling.
• Develop algorithms for optical propagation, radiometry, image formation, and observable phenomenology.
• Build models that support analysis of physical scenes, signatures, and remote observations.
• Collaborate with physicists, engineers, software developers, mathematicians, AI/ML researchers, and systems engineers to solve complex technical problems.
• Serve as a technical bridge between teams by translating concepts, assumptions, requirements, and analysis results across disciplines.
• Validate models through analysis, simulation, and comparison with experimental, engineering, or operational data.

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

• Possess a Ph.D. in Physics, Applied Physics, Mechanical Engineering, Aerospace Engineering, or another closely related technical field
• Have 2+ years of relevant  physics, mathematics, numerical methods, computational problem solving, or physics-based modeling.
• Have strong programming experience in at least one scientific or general-purpose programming language.
• Are able to rapidly learn new technical subjects and apply that knowledge to interdisciplinary engineering problems.
• Have excellent written and verbal communication skills and can explain complex technical ideas to both specialists and multidisciplinary audiences.
• Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Top 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.

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://(Use the "Apply for this Job" box below)..

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…