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Engineering, Computer Science, or a related field. Accompanying Knowledge, Skills, Abilities and Competencies Excellent abilities in molecular modeling and simulations (molecular dynamics or Monte Carlo
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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USNH Employees should apply within Workday through the Jobs Hub app The research position(s) are within the broad area of biophysics, structural modeling, and molecular dynamics (MD) simulations
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molecular tools, capsid architectural modeling, classical nucleation theory, molecular dynamics simulations, and protein expression. The ideal candidate will have a background in mathematical biology
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research codebase and data; excellent verbal and written communication skills; and a collaborative mentality towards research and mentoring. Desired skills and techniques include Molecular Dynamics
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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preferred, but not required) are desired. Experiences with catalysis (biological, homogeneous, or heterogeneous), excited-state simulation methods, multiscale simulations (broadly defined), molecular dynamics
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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. Quantum Mechanical Calculations: - Performing first-principles based or Density Functional Theory (DFT) calculations for molecules/materials and interphases - Utilizing Molecular Dynamics (MD) simulations
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papers and reports. We are looking for: Ph.D. in Chemistry/Physics/Materials Science, or similar fields. Density Functional Theory, Molecular Dynamics (ab-initio MD and/or nonadiabatic MD), Kinetic