From Johns Hopkins Applied Physics Laboratory's posting. “We” and “our” refer to the employer.
Description
Are you a creative person driven to solve new problems?
Are you searching for impactful work in computational engineering and research that doesn’t confine you to working on the same thing year after year?
Does using atomistic and multiscale modeling to understand, design, and optimize advanced alloys and ceramics for aerospace, sensing, or energy-storage applications sound like a dream job?
If so, we’re looking for someone like you to join our team at APL.
We are seeking a Computational Materials Scientist to develop and apply atomistic and multiscale computational methods to understand and predict the behavior of inorganic materials, particularly advanced metal alloys and ceramics. You will model key physical processes, from atomic-scale structure, defecFts, and chemical interactions to effective material properties, to solve impactful challenges in aerospace, sensing, energy storage, and other applications.
As a member of our team, you will contribute to exciting projects supporting the US Department of War and other government agencies. Our team strives to develop, apply, and maintain deep expertise in multiscale modeling techniques that give insight across key length and time scales. You will work alongside analysts, laboratory scientists, and engineers who have a passion for applying our modeling results to physical systems that advance the state of the art and have real-world impact.
As a Computational Materials Scientist, you will:
Develop and use models of metals and ceramics to determine relationships between structure and function across a variety of length and time scales, from atomic-scale lattice structure and defects through phase and microstructure evolution to effective engineering properties.
Leverage modeling methods including classical molecular dynamics, electronic structure, reaction pathway and kinetic modeling, coarse graining, enhanced sampling, statistics, and machine learning models.
Design and apply scalable computational workflows to accelerate materials discovery and optimization through high-throughput simulation, data-driven analysis, and physics-based modeling.
Quantify uncertainty, validate predictions against experimental data, and assess model applicability across relevant materials and operating conditions.
Actively collaborate with analysts, scientists, and engineers on a day-to-day basis to guide materials discovery and interpret experimental observations.
Propose future projects and initiatives.
Craft reports and give presentations to communicate results to team members and government partners.
We’re looking for talented and versatile computational researchers who are excited to expand their analytical toolbox. If you have experience in any of the methods or tools above, and are motivated to learn even more, we want to talk to you.
Qualifications
You meet our minimum qualifications for the job if you...
A Ph.D. in Materials Science, Chemistry, Mechanical Engineering, Chemical Engineering, Physics, Applied Mathematics, or equivalent with demonstrated application of knowledge to answer complex questions.
3+ years of experience in performing physics-based simulations of fundamental properties in inorganic solid materials, such as electronic structure calculations or classical/ab initio molecular dynamics.
Scientific/engineering programming experience, with the ability to work in multiple languages (MATLAB, C/C++, Python, FORTRAN, …) and with algorithms commonly used in computational science and engineering.
Demonstrated ability to work both independently and collaboratively within a multidisciplinary team and incorporate multiple experimental data types into computational workflows
Ability to manage and prioritize across multiple projects.
Excellent verbal and written communication skills.
Willingness and ability to travel occasionally to attend meetings or tests at other government and contractor sites.
Ability to work in closed area facilities.
Ability to obtain a Secret level security 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...
Experience in applying and/or developing machine learning models in conjunction with physics-based simulations to solve problems involving design or selection of inorganic materials.
Experience developing models of inorganic materials, such as metal alloys or ceramic materials, that convey information across models at different length/time scales or physics.
Experience modeling chemical reactions, reaction pathways, thermodynamics, or kinetics using atomistic simulation methods.
Experience modeling inorganic materials and their environmental interactions for specific applications in aerospace, sensing, or energy storage and conversion, corrosion, catalysis, or extreme environments.
Experience applying large language models and tool-enabled AI agents to scientific reasoning tasks including automated hypothesis generation, formal reasoning, and workflow automation.
Experience in algorithm development for accelerating materials science or chemistry calculations on noisy, intermediate-scale quantum (NISQ) devices.
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
$105,000 Annually
Maximum Rate
$290,000 Annually
Responsibilities
Are you a creative person driven to solve new problems?
Are you searching for impactful work in computational engineering and research that doesn’t confine you to working on the same thing year after year?
Does using atomistic and multiscale modeling to understand, design, and optimize advanced alloys and ceramics for aerospace, sensing, or energy-storage applications sound like a dream job?
If so, we’re looking for someone like you to join our team at APL.
We are seeking a Computational Materials Scientist to develop and apply atomistic and multiscale computational methods to understand and predict the behavior of inorganic materials, particularly advanced metal alloys and ceramics. You will model key physical processes, from atomic-scale structure, defecFts, and chemical interactions to effective material properties, to solve impactful challenges in aerospace, sensing, energy storage, and other applications.
As a member of our team, you will contribute to exciting projects supporting the US Department of War and other government agencies. Our team strives to develop, apply, and maintain deep expertise in multiscale modeling techniques that give insight across key length and time scales. You will work alongside analysts, laboratory scientists, and engineers who have a passion for applying our modeling results to physical systems that advance the state of the art and have real-world impact.
As a Computational Materials Scientist, you will:
Develop and use models of metals and ceramics to determine relationships between structure and function across a variety of length and time scales, from atomic-scale lattice structure and defects through phase and microstructure evolution to effective engineering properties.
Leverage modeling methods including classical molecular dynamics, electronic structure, reaction pathway and kinetic modeling, coarse graining, enhanced sampling, statistics, and machine learning models.
Design and apply scalable computational workflows to accelerate materials discovery and optimization through high-throughput simulation, data-driven analysis, and physics-based modeling.
Quantify uncertainty, validate predictions against experimental data, and assess model applicability across relevant materials and operating conditions.
Actively collaborate with analysts, scientists, and engineers on a day-to-day basis to guide materials discovery and interpret experimental observations.
Propose future projects and initiatives.
Craft reports and give presentations to communicate results to team members and government partners.
We’re looking for talented and versatile computational researchers who are excited to expand their analytical toolbox. If you have experience in any of the methods or tools above, and are motivated to learn even more, we want to talk to you.
Qualifications
You meet our minimum qualifications for the job if you...
A Ph.D. in Materials Science, Chemistry, Mechanical Engineering, Chemical Engineering, Physics, Applied Mathematics, or equivalent with demonstrated application of knowledge to answer complex questions.
3+ years of experience in performing physics-based simulations of fundamental properties in inorganic solid materials, such as electronic structure calculations or classical/ab initio molecular dynamics.
Scientific/engineering programming experience, with the ability to work in multiple languages (MATLAB, C/C++, Python, FORTRAN, …) and with algorithms commonly used in computational science and engineering.
Demonstrated ability to work both independently and collaboratively within a multidisciplinary team and incorporate multiple experimental data types into computational workflows
Ability to manage and prioritize across multiple projects.
Excellent verbal and written communication skills.
Willingness and ability to travel occasionally to attend meetings or tests at other government and contractor sites.
Ability to work in closed area facilities.
Ability to obtain a Secret level security 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...
Experience in applying and/or developing machine learning models in conjunction with physics-based simulations to solve problems involving design or selection of inorganic materials.
Experience developing models of inorganic materials, such as metal alloys or ceramic materials, that convey information across models at different length/time scales or physics.
Experience modeling chemical reactions, reaction pathways, thermodynamics, or kinetics using atomistic simulation methods.
Experience modeling inorganic materials and their environmental interactions for specific applications in aerospace, sensing, or energy storage and conversion, corrosion, catalysis, or extreme environments.
Experience applying large language models and tool-enabled AI agents to scientific reasoning tasks including automated hypothesis generation, formal reasoning, and workflow automation.
Experience in algorithm development for accelerating materials science or chemistry calculations on noisy, intermediate-scale quantum (NISQ) devices.
About this listing
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
