Computational Materials Science Researcher (DFT & Molecular Dynamics)

We are looking for a motivated and capable researcher in Computational Materials Science with an MSc/PhD background (or current PhD enrollment) in Materials Science and Engineering.

Key Responsibilities

• Translate materials problems into computational studies by selecting the appropriate method, level of theory, model size, and timescale.
• Design and perform first-principles calculations using VASP to study structural, mechanical, thermal, electronic, and thermodynamic properties.
• Set up, run, and analyze Molecular Dynamics simulations using LAMMPS, including selecting and validating interatomic potentials.
• Validate results through convergence tests, functional and pseudopotential choices, and potential-transferability checks.
• Develop and automate DFT/MD workflows by writing Python code for input generation, job submission, data extraction, post-processing, analysis, and visualization.
• Compare computational results with experimental data, theoretical models, and published literature; identify limitations and propose follow-up work.
• Contribute to technical reports and scientific publications.

Required Qualifications

• PhD degree or current PhD enrollment in Materials Science and Engineering.
• Strong programming skills in Python, including developing, debugging, and documenting scientific code.
• Practical experience with VASP and a solid understanding of Density Functional Theory (DFT).
• Practical experience with LAMMPS and a solid understanding of Molecular Dynamics (MD).
• Ability to independently design, execute, troubleshoot, and analyze computational materials science projects.
• Strong analytical, problem-solving, and scientific communication skills.

Preferred Qualifications

• Experience with ASE, pymatgen, phonopy, or the OVITO Python API.
• Familiarity with machine-learning interatomic potentials (e.g., MACE, NequIP, DeePMD).
• Experience with Git and HPC job schedulers (Slurm/PBS).
• Publications in computational materials science.

How to Apply

• CV with a list of publications, thesis, research projects, or completed simulations.
• A GitHub link with sample projects and Python code; if you have no GitHub, at least one relevant work sample is required.