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2024 PhD Graduate - Post Doctoral Fellow Computational MaterialsScientist/Chemistry

The Johns Hopkins University Applied Physics Laboratory | Laurel, MD, US, 20723

Posted 10 hours ago


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Description

Description

Do you have a fundamental drive and fascination in solving problems of all kinds?

Are you searching for impactful work in computational materials science that doesn't confine you to working on the same thing year after year?

Does making meaningful contributions to projects that span submarines, surface ships, UAVs, aircraft, missiles, and spacecraft sound like a dream job?

Are you a creative person who likes to tackle unique problems, think in terms of the driving physics, gather interdisciplinary teams, and generate complex new solutions?

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

We are seeking a computational scientist to help us provide insight to the physical processes that define the behaviors of physical systems. As a member of our team, you will contribute to exciting projects supporting organizations such as the US Department of Defense and NASA. Our team strives to develop and apply deep expertise in multiscale modeling techniques across many length and time scales. You will work alongside both computational and experimental colleagues to develop new concepts and advance them toward solving real problems.

As a Computational Materials Science/Chemistry Post-Doctoral Fellow:
  • Your primary responsibility will be to develop both physics-based and data-driven models of materials and utilize them to understand and guide material development for complex systems.
  • You will interface with and actively collaborate with engineers, designers, fabricators, and scientists on a day to day basis.
  • You will propose and develop new modeling frameworks (e.g. based on machine learning techniques) for predicting the response of complex systems to conditions including but not limited to mechanical, thermal, chemical, and electromagnetic stimulus.
  • You will craft reports and give presentations to communicate results to team members and government partners.

Qualifications

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

  • A PhD in Materials Science, Chemistry, Physics, Applied Mathematics, or equivalent with demonstrated application of knowledge.
  • Expertise developing physics-based simulations and applying data analysis to solve problems in materials science, chemistry, physics, or biology and the ability to contribute to development of those methods.
  • Experience in performing calculations on materials to model atomic-scale phenomena in organic or inorganic systems.
  • Scientific/engineering programming experience, the ability to work in multiple languages (MATLAB, C/C++, Python, FORTRAN, etc,) and algorithms commonly used in computational science and engineering.
  • Familiarity with concepts in machine learning and data science.
  • Ability to work independently on multiple projects with little guidance and direction and work collaboratively within a multidisciplinary team environment.
  • Excellent oral and written communication skills.
  • Ability to travel occasionally for meetings or tests at other government and contractor sites.
  • Ability to work in closed area facilities.
  • Ability to obtain an Interim Secret clearance to start and a final 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 have...

  • 2+ years of work experience in computational physics, chemistry, or materials science.
  • Experience in developing calculations using density functional theory and/or molecular dynamics to model and predict properties of materials.
  • Experience contributing to proposals for research funding.
  • Fluency in commonly-used libraries for machine learning and data science.
  • Extensive experience in the development and use of simulation software in computational engineering and science.
  • Experience using hardware accelerators (e.g. GPUs) and familiarity with parallel programming techniques (MPI/OpenMP).
  • Demonstrated ability to contribute to team-based software development.

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 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


About Us

APL is an Equal Opportunity/Affirmative Action employer. 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 promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are 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 . Only by ensuring that everyone's voice is heard are we empowered to be bold, do great things, and make the world a better place.

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