We are seeking a highly motivated Molecular Dynamics Intern to join our research team. This internship provides hands-on experience in computational modeling, molecular simulations, and advanced data analysis techniques. The intern will work on exciting projects involving molecular interactions, protein-ligand binding, and simulation-driven insights for real-world applications.
Qualifications
Currently pursuing a Bachelor’s, Master’s, or PhD in Computational Biology, Biophysics, Chemistry, Bioinformatics, or a related field.
Hands-on experience with molecular dynamics simulations and force fields (e.g., AMBER, CHARMM, OPLS).
Proficiency in scripting languages like Python, R, or Bash for data analysis and automation.
Familiarity with molecular visualization tools such as VMD, PyMOL, or Chimera.
Strong analytical and problem-solving skills with an ability to interpret complex simulation data.
Effective communication and collaboration skills.
Experience with GPU-accelerated MD simulations (CUDA, OpenMM).
Knowledge of free energy calculations, docking, and machine learning applications in molecular modeling.
Exposure to cloud computing or high-performance computing (HPC) environments.
Responsibilities
Perform molecular dynamics (MD) simulations of biomolecular systems (proteins, nucleic acids, small molecules, etc.).
Develop and optimize simulation workflows using tools like GROMACS, AMBER, CHARMM, or OpenMM.
Analyze MD trajectories for structural dynamics, binding affinities, and thermodynamic properties.
Utilize enhanced sampling techniques (e.g., metadynamics, umbrella sampling) to explore complex biomolecular behavior.
Assist in scripting and automation for data analysis using Python, Bash, or MATLAB.
Collaborate with cross-functional teams, including computational chemists, structural biologists, and data scientists.
Document findings and present research progress to the team.