Physical Sciences Expert at Turing

Physical Sciences Expert | Pay: Varies | Remote

Turing is seeking Physical Sciences experts to develop terminal-based scientific tasks for Terminal Bench Science. You will translate authentic physics, chemistry, materials science, astronomy, and computational science workflows into reproducible benchmark environments, helping evaluate whether AI agents can reason through scientific problems, operate command-line tools, debug calculations, and produce reliable scientific artifacts.

About the Role

You will create scientific inputs, computational models, executable solutions, automated tests, and objective grading criteria for realistic, multi-step terminal tasks.

Key Responsibilities

• Design multi-step terminal tasks based on realistic physical-science workflows.
• Develop self-contained computational environments with pinned dependencies and scientific software.
• Create input datasets, molecular structures, simulation parameters, experimental data, or model configurations.
• Implement expert solutions using Python, Bash, C/C++, Julia, or domain-specific tools.
• Develop automated tests for numerical accuracy, physical consistency, convergence, and output structure.
• Create tasks involving simulations, numerical modeling, data fitting, optimization, spectroscopy, molecular analysis, or scientific visualization.
• Define numerical tolerances, units, boundary conditions, and expected scientific behavior.
• Validate that tasks are reproducible and execute without runtime downloads.
• Debug issues involving dependencies, precision, solver stability, performance, and file formats.
• Communicate scientific assumptions and computational limitations clearly to reviewers.

Core Domains

Physics, chemistry, materials science, computational physics, computational chemistry, astronomy, thermodynamics, quantum mechanics, statistical mechanics, or materials modeling.

Required Qualifications

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in a relevant physical-science discipline.
• Strong programming skills in Python, C/C++, Julia, Bash, or another scientific programming language.
• Experience working in Linux or terminal-based environments.
• Experience with numerical methods, scientific modeling, simulations, or quantitative data analysis.
• Ability to create and validate computational scientific workflows independently.
• Strong understanding of units, numerical precision, physical constraints, and scientific reproducibility.

Preferred Qualifications

• Experience with NumPy, SciPy, pandas, matplotlib, SymPy, JAX, or similar libraries.
• Familiarity with molecular dynamics, quantum chemistry, finite-difference methods, Monte Carlo methods, optimization, or statistical modeling.
• Experience with tools such as OpenMM, ASE, RDKit, Psi4, LAMMPS, GROMACS, or other domain-specific software.
• Familiarity with Docker, Conda, Git, CI systems, and automated testing.
• Experience with HPC systems or performance-sensitive scientific workloads.

Bonus Points

• Experience evaluating AI coding or terminal agents.
• Research software engineering experience.
• Experience creating benchmark tasks or automated graders.
• Publications or open-source contributions involving computational science.
• Experience converting experimental or research workflows into reproducible packages.

Pay rate, schedule, and contract terms are not specified in the source listing.