Computational Chemistry Problem Designer, PhD

Obsidian; Austin (TX); On-site; USD 90,000 - 130,000; Part time

Job summary

Obsidian seeks a Computational Chemistry & Electronic Structure Expert to design large-scale benchmarks evaluating AI systems on real scientific workflows. You will craft graduate-level problems using PySCF and related tools, run simulations, interpret results, and design experiments to uncover hidden information from data.

Ideal candidates have MS or PhD level training in a relevant STEM field, hands-on software experience, and strong Python skills.

Qualifications

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience)
• Proven proficiency with at least one listed scientific software library (e.g., PySCF) shown through publications or projects
• Strong Python skills — you'll be writing problem setups, oracle functions, and solution validators
• Ability to work independently and refine problem designs based on feedback
• Comfortable working in a Linux/terminal environment with remote compute sandboxes
• Available for at least 15–20 hours per week

Responsibilities

• Create graduate-level problems that require skilled use of specialized scientific software
• Test problems against state-of-the-art AI models and refine until target difficulty is reached
• Design problems around excited-state analysis, orbital diagnostics, and method choices for complex electronic structures
• Interpret computational results and artifacts to design robust challenges

Skills

Python

Graduate-level training

Independent work

Problem design

Education

MS or PhD in relevant STEM

Tools

PySCF

Job description

Obsidian seeks a Computational Chemistry & Electronic Structure Expert to design large-scale benchmarks evaluating AI systems on real scientific workflows. You will craft graduate-level problems using PySCF and related tools, run simulations, interpret results, and design experiments to uncover hidden information from data.

Ideal candidates have MS or PhD level training in a relevant STEM field, hands-on software experience, and strong Python skills.