2027 PhD Graduate - Modeling and Simulation Analyst - Air Combat and Strike Mission Analysis Group

The Johns Hopkins University Applied Physics Laboratory

Laurel (MD)

On-site

USD 105,000 - 245,000

Full time

6 days ago

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Benefits offered by this job

Retirement plans

Paid time off

Medical

Dental

Vision

Life insurance

Short-term disability

Long-term disability

Flexible spending accounts

Education assistance

Training and development

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) seeks scientists and engineers to model and simulate air combat systems, strike weapons, and multi-domain sensing for mission-level analysis. You will build and apply modeling tools to inform requirements, acquisitions, and force design, collaborating with a multidisciplinary team in a defense-focused environment.

Minimum qualifications include a PhD in a technical field, experience with modeling/simulation, and proficiency in Python,

Qualifications

PhD in engineering, physics, computer science, applied mathematics, operations research or related field.
Experience developing or applying models and simulations through coursework, research, internships, or projects.
Experience with Python, MATLAB, C++, or similar.
Strong analytical and problem-solving skills; able to apply technical concepts to operational problems.
Ability to work independently and in multidisciplinary teams; clear communication.
Eligible for Interim Secret clearance with goal of TS clearance; U.S. citizenship required.

Responsibilities

Build, integrate, test, and improve models of aircraft, weapons, sensors, countermeasures, communications, and other mission systems.
Apply AFSIM and other tools to analyze air combat and precision strike missions.
Design simulation experiments and evaluate performance at multiple system levels.
Use MATLAB, Python, and other software to automate simulations, process data, visualize results, and improve workflows.
Collaborate with engineers, military operators, program offices, and decision-makers to frame questions and communicate findings.

Skills

Python

MATLAB

C++

Analytical

Security clearance

Teamwork

Education

PhD in engineering/physics/CS/OR

Tools

AFSIM

Job description

Description

Do you want to help shape the next generation of air combat systems and strike weapons?

Are you interested in using modeling and simulation to answer questions about military effectiveness, system requirements, and future force design? We are looking for someone like you to join our team!

We are seeking candidates with initiative and intellectual curiosity to evaluate the development and employment of air combat systems, strike weapons, countermeasures, and multi-domain sensing and communications. You will build and apply modeling and simulation tools to conduct mission-level analysis that inform system requirements, acquisition decisions, military utility assessments, and force design.

Our team of more than 50 analysts and computer scientists performs mission-level analysis for Department of War programs. We work collaboratively, invest in staff development, and deliver objective analysis to support important technical and operational decisions.

As a member of our team, you will:

Build, integrate, test, and improve models of aircraft, weapons, sensors, countermeasures, communications, and other mission systems
Apply AFSIM and other tools to analyze air combat and precision strike missions in contested environments
Design simulation experiments and evaluate performance at the individual system, system-of-systems, and force-structure levels
Use MATLAB, Python, and other software tools to automate simulations, process data, visualize results, and improve analytical workflows
Work with engineers, military operators, program offices, and decision-makers to frame analytical questions and communicate findings, limitations, and recommendations

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

Possess a PhD degree in engineering, physics, computer science, applied mathematics, operations research, or another related technical field
Have experience developing or applying models and simulations through coursework, research, internships, employment, or independent projects
Have experience using Python, MATLAB, C++, or another programming language
Have analytical and problem-solving skills and an interest in applying technical concepts to operational problems
Can work independently, collaborate as part of a multidisciplinary team, and communicate technical information clearly
Are able to obtain an Interim Secret-level security clearance by your start date and 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.

You’ll go above and beyond our minimum requirements if you...

Have experience using AFSIM or another campaign, mission, or engagement-level simulations
Have experience designing simulation experiments, analyzing large datasets, or applying statistical methods
Are proficient in Python, MATLAB, C++, or another language used for scientific computing, data analysis, or modeling and simulation
Have knowledge of military aviation, air combat, precision strike, weapons, sensors, countermeasures, communications, or intelligence, surveillance, reconnaissance, and tracking systems
Hold an active Secret or higher-level security 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 https://www.jhuapl.edu/careers.

robust education assistance program
unparalleled retirement contributions
healthy work/life balance

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.