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About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About The Role
We are looking for a Physical Sciences expert to develop realistic, terminal-based scientific tasks for an AI benchmarking project. You will translate authentic workflows across physics, chemistry, materials science, astronomy, computational physics, and computational chemistry into reproducible environments that test whether AI agents can reason through scientific problems, use command-line tools, debug calculations, and produce reliable scientific outputs.
The role combines scientific expertise, programming, simulation, and computational workflow design, with a strong focus on numerical accuracy, physical consistency, reproducibility, and objective evaluation.
Core Domains
Physics
Chemistry
Materials Science
Computational Physics
Computational Chemistry
Astronomy
Thermodynamics
Quantum Mechanics
Statistical Mechanics
Materials Modeling
Key Responsibilities
Design multi-step terminal-based 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, and model configurations.
Implement expert reference 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, and scientific visualization.
Define appropriate numerical tolerances, units, boundary conditions, and expected scientific behavior.
Validate that tasks are reproducible and execute successfully without runtime downloads.
Debug issues involving dependencies, numerical precision, solver stability, performance, and file formats.
Document scientific assumptions, expected behavior, and computational limitations for reviewers
Requirements
Ph.D., postdoctoral experience, or equivalent advanced technical experience in physics, chemistry, materials science, astronomy, computational science, or a related field.
Strong programming skills in Python, C/C++, Julia, Bash, or another scientific programming language.
Experience working in Linux or terminal-based environments.
Hands-on experience with numerical methods, scientific modeling, simulations, or quantitative data analysis.
Ability to independently create and validate reproducible computational scientific workflows.
Strong understanding of units, numerical precision, physical constraints, and scientific reproducibility.
Experience developing, debugging, or validating scientific computational models or workflows
Work arrangement
Yes
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