Particle & Nuclear Physics Computational Problem Designer [Remote]

This role focuses on designing innovative computational problems that challenge AI systems to utilize scientific software tools effectively. You will create graduate-level tasks grounded in real scientific workflows, ensuring that AI models can solve complex research-grade problems, from querying simulations to interpreting outputs and designing experimental strategies. Key Responsibilities

• Design computational problems that require advanced use of domain-specific scientific software libraries.
• Develop tasks that test solvers on multi-step scientific workflows, ensuring precise outputs from fully specified setups.
• Create sequences of queries or experiments to uncover hidden information, requiring strategic reasoning about measurements and interpretations.
• Engage in a calibration loop for each task, testing against state-of-the-art AI models and refining designs to meet targeted difficulty levels.

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

• Particle & Nuclear Physics: Proficiency with scikit-hep and related HEP Python tools for particle physics data analysis, cross-section computations, renormalization group calculations, and perturbative QCD. Experience with Monte Carlo event generation or collider phenomenology is a plus.

The ideal candidate will possess graduate-level expertise (MS or PhD preferred) in the specified domain, with substantial hands-on experience using relevant software tools. You should have:

• Written code that utilizes these libraries to address real research problems, understanding their limitations and edge cases.
• The ability to design problems that emphasize reasoning strategy over brute computation, where multiple approaches exist but careful analysis is required to find the correct solution.

• Graduate-level training in a relevant STEM domain (MS, PhD, or equivalent research experience).
• Demonstrated proficiency with at least one of the listed scientific software libraries, supported by research publications, open-source contributions, or professional experience.
• Strong Python programming skills for writing problem setups, oracle functions, and solution validators.
• Ability to work independently and iterate on problem designs based on calibration feedback.
• Comfort 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 pedagogy or exam/problem-set design.
• Experience with computational reproducibility and containerized environments.