About this role
As a Particle & Nuclear Physics Expert, you will play a pivotal role in developing a large-scale benchmark aimed at evaluating the capabilities of advanced AI systems in solving 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 for research-level tasks, including running simulations, interpreting results, designing experiments, and extracting hidden insights from data.
This role transcends typical data-labeling tasks. You will create original, graduate-level problems grounded in authentic scientific workflows, rigorously test them against state-of-the-art AI models, and refine them to achieve the ideal level of difficulty.
Key Responsibilities- Design problems requiring proficient use of specialized scientific software, including tasks that challenge AI to compute precise answers from well-defined setups.
- Develop more complex problems where AI must strategically plan queries or experiments to reveal information that is not immediately visible.
- Iterate through a testing loop with advanced AI models, refining each problem until it meets the target difficulty.
We are particularly interested in candidates with extensive hands-on experience in:
- Particle & Nuclear Physics, utilizing 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 relevant domain, coupled with practical experience using these tools. You should have a history of writing code with these libraries to tackle real research problems, along with a deep understanding of their limitations and edge cases. A strong candidate will approach problem design like a puzzle creator, crafting challenges that require intelligent reasoning rather than mere computation.
Requirements- Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
- Proven proficiency with at least one of the specified scientific software libraries, demonstrated through 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 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.