About The Position

We are looking for a motivated summer intern to work at the intersection of structure generation, optimizations, and genetic algorithms. The intern will contribute to the development and evaluation of specific optimization routes, with a particular interest in applications related to structure generation of gas-phase and solid-state structures. This role is ideal for students who enjoy combining genetic algorithms, optimizations, and code development to solve complex scientific or engineering problems.

Requirements

  • Currently enrolled in a Master's, or Ph.D. program in Materials Science, Chemical Engineering, Physics, Computer Science, Computational Chemistry, or a related field.
  • Hands-on experience developing optimizations, such as genetic algorithms or similar methods.
  • Strong programming skills (primarily Python).
  • Excellent problem-solving skills and a strong analytical mindset.
  • Ability to work independently and as part of a team.

Nice To Haves

  • Knowledge or practical experience with genetic algorithms.
  • Experience with code developments to implement new features into an existing code base
  • Familiarity with numerical methods and scientific computing libraries (e.g., ASE, pymatgen, scikit-learn, PyTorch).
  • Familiarity with fundamental concepts in materials science (e.g., crystallography, bonding, material properties).
  • Experience working in research-oriented or interdisciplinary environments.

Responsibilities

  • Design, develop, setup and evaluate optimizers/genetic algorithms
  • Prepare and process relevant materials data (e.g., structural databases, property datasets) for use in genetic algorithm workflows
  • Assist with structural exploration in both gas-phase and solid-state regimes
  • Analyze model performance and document findings clearly
  • Collaborate with researchers/engineers across code development and structural analysis
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