Gramian Consulting
Gramian Consulting
Gramian Consulting is a remote-first consulting firm focused on engineering, data, and AI talent. It helps organizations expand technical capacity through talent augmentation, recruiting, dedicated teams, and contractor management, while providing services such as LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure. The firm also supports individual career development through mentorship and education programs covering career readiness, interview preparation, and international market orientation. Its work combines hands-on engineering and recruiting experience to help clients build technical teams and apply AI to business needs.

Physical Sciences Computational Research Specialist – Turkey Remote

Develop terminal-based scientific tasks and reproducible computational workflows for Gramian Consulting’s AI benchmarking project. Build simulations, reference solutions, and automated validation for physical-science applications.

Description

  • Create multi-step terminal tasks modeled on practical physical-science workflows.
  • Build self-contained environments with pinned dependencies and scientific software.
  • Prepare datasets, molecular structures, simulation settings, experimental results, and model configurations.
  • Develop reference implementations with Python, Bash, C/C++, Julia, or specialized scientific tools.
  • Write automated checks for numerical accuracy, physical validity, convergence, and output formatting.
  • Design tasks covering simulation, numerical modeling, data fitting, optimization, spectroscopy, molecular analysis, and scientific visualization.
  • Set suitable numerical tolerances, units, boundary conditions, and expected scientific outcomes.
  • Confirm that workflows are reproducible and run successfully without downloading resources at runtime.
  • Troubleshoot dependencies, numerical precision, solver stability, performance, and file-format issues.
  • Record scientific assumptions, expected results, and computational limitations for reviewers.

Requirements

  • Doctorate, postdoctoral training, or equivalent advanced technical experience in physics, chemistry, materials science, astronomy, computational science, or a related discipline.
  • Proficiency in Python, C/C++, Julia, Bash, or another language used for scientific programming.
  • Practical experience with Linux and terminal-based development environments.
  • Experience applying numerical methods, scientific modeling, simulations, or quantitative data analysis.
  • Ability to independently build and verify reproducible computational science workflows.
  • Solid knowledge of measurement units, numerical precision, physical constraints, and scientific reproducibility.
  • Experience developing, debugging, or validating computational models or workflows in a scientific context.

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