Computational Physicist – Physics-Based Scene and Signature Modeling

Johns Hopkins Applied Physics Laboratory•Laurel, MD

8d•Onsite

About The Position

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.

Requirements

Possess a Ph.D. in Physics, Applied Physics, Mechanical Engineering, Aerospace Engineering, or another closely related technical field
Have 2+ years of relevant experience.in 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.

Responsibilities

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.