As a Computational Chemistry & Electronic Structure Expert, you will play a pivotal role in developing a large-scale benchmark aimed at evaluating the capabilities of advanced AI systems in tackling complex scientific and engineering challenges. Your primary responsibility will be to design intricate computational problems that assess whether AI can effectively utilize real scientific software to conduct research-level tasks, including running simulations, interpreting results, and designing experiments.

• Create original, graduate-level computational problems based on authentic scientific workflows.
• Test and refine these problems against cutting-edge AI models to ensure they meet the desired difficulty level.
• Design problems that require the adept use of specialized scientific software, including tasks that involve computing exact answers from defined setups and planning strategic queries or experiments.
• Engage in a testing loop with state-of-the-art AI models, iterating on problem designs until they achieve the target complexity.

We are particularly interested in candidates with extensive, hands-on experience in:

• Computational Chemistry & Electronic Structure , Proficiency with PySCF for quantum chemistry calculations, including Hartree-Fock, DFT, TDDFT, CASSCF, and post-HF methods. Candidates should be capable of designing problems related to excited-state analysis, orbital diagnostics, and interpreting computational artifacts.

• Graduate-level expertise (MS or PhD preferred) in a relevant STEM field, with practical experience using the specified tools.
• Demonstrated proficiency with at least one of the scientific software libraries through research publications, open-source contributions, or professional work.
• Strong Python programming skills for writing problem setups, oracle functions, and solution validators.
• Ability to work independently and refine problem designs based on feedback.
• Comfortable operating in a Linux/terminal environment with remote compute sandboxes.
• Availability for at least 15, 20 hours per week.

• Experience across multiple listed domains or tools.
• Familiarity with benchmark or evaluation design.
• Background in scientific teaching or exam/problem-set design.
• Experience with computational reproducibility and containerized environments.

Please note that this application includes a coding assessment as part of the evaluation process.