• PhD degree in Science or Engineering
• Education or a track record in applied mathematics, with a strong interest in physical sciences
• A solid foundation in thermodynamics & statistical mechanics, solid-state physics/chemistry, and/or quantum mechanics
• Practical experience with density functional theory calculations (e.g., VASP, Quantum Espresso, Q-Chem, PySCF)
• Proficiency in at least one mainstream deep learning framework (e.g., PyTorch, JAX)
• Expertise in (atomistic) thermodynamic, kinetic simulations or computational chemistry
• Ability to independently design and execute research projects and excellent proficiency in written and oral English.
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