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Physical Sciences Expert Terminal Bench

Exclusive opportunity

Remote

Physical Sciences Expert Terminal Bench

Crossing Hurdles

Physical Sciences Expert Terminal Bench

Skills

PythonNumPypandasData AnalysisLinux

18 days ago

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Important information


Contract type:

Permanent

Salary:

₹6,000,000 – ₹7,500,000 / year

Location:

Gurugram, Haryana, India

Work mode:

Remote

Published on:

7 October 2026

What they need


Role & 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 solutions using Python, Bash, C/C++, Julia, or domain-specific scientific 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 numerical tolerances, units, boundary conditions, and expected scientific behavior.
  • Validate that tasks are reproducible and execute successfully without runtime downloads.
  • Debug dependencies, precision, solver stability, performance, and file-format issues.

Preferred candidate profile

  • Ph.D., postdoctoral experience, or equivalent advanced technical experience in a relevant physical-science discipline.
  • Strong expertise in Physics, Chemistry, Materials Science, Computational Physics, Computational Chemistry, Astronomy and Cosmology, Thermodynamics, Quantum Mechanics, Statistical Mechanics, or Materials Modeling.
  • 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 scientific data analysis.
  • Ability to independently create and validate computational scientific workflows.
  • Strong understanding of units, numerical precision, physical constraints, and scientific reproducibility.
  • Familiarity with scientific libraries such as NumPy, SciPy, pandas, matplotlib, SymPy, or JAX is preferred.

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