Multiscale Soft Matter Modeling Scientist

Johns Hopkins Applied Physics Lab; Laurel (MD); On-site; USD 105,000 - 290,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory in Laurel, Maryland seeks a Computational Soft Matter Researcher to model key processes in complex soft-material systems such as polymers. You will contribute to projects supporting DoD and other government agencies, developing deep expertise in multiscale modeling across length and time scales.

You will work with analysts, scientists, and engineers using MD, computational chemistry, coarse graining, and ML techniques.

Qualifications

• PhD in a quantitative field with demonstrated application to complex questions.
• 3+ years of physics-based macromolecule simulations.
• Ability to work independently and in multidisciplinary teams.
• Strong verbal and written communication skills.
• Willingness to travel occasionally and obtain security clearance.

Responsibilities

• Develop and apply models of macromolecules across length/time scales.
• Analyze macromolecular characteristics including thermodynamic and electromagnetic phenomena.
• Collaborate with analysts, scientists, and engineers daily.
• Propose future projects and initiatives.
• Prepare reports and present results to government partners.

Skills

Physics-based simulations

MD/PhD-level research

Communication skills

Travel willingness

GPU/parallel computing

Programming

Team collaboration

Education

Ph.D. in Biochemical, Chemical or Mechanical Engineering, Biology, Chemistry, Physics, Applied Mathematics, or equivalent

Tools

MATLAB

C/C++

Python

FORTRAN

MPI/OpenMP

GPU acceleration

Job description

Johns Hopkins Applied Physics Laboratory in Laurel, Maryland seeks a Computational Soft Matter Researcher to model key processes in complex soft-material systems such as polymers. You will contribute to projects supporting DoD and other government agencies, developing deep expertise in multiscale modeling across length and time scales.

You will work with analysts, scientists, and engineers using MD, computational chemistry, coarse graining, and ML techniques.