Applied Mathematics, Scientific Computing Specialist
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Job Description
Applied mathematics specialist developing reproducible computational tasks for Gramian Consultancy’s AI benchmarking project. Implementing algorithms, automated tests, and rigorous numerical evaluation criteria.
Responsibilities:
- Design authentic, multi-step computational mathematics tasks based on real-world research and mathematical workflows.
- Translate mathematical problems into self-contained, reproducible terminal environments.
- Prepare datasets, equations, model definitions, constraints, initial conditions, and expected outputs.
- Implement expert reference solutions using Python, R, Julia, C/C++, Bash, or other relevant tools.
- Develop tasks involving optimization, numerical integration, differential equations, matrix computation, statistical inference, stochastic modeling, and algorithm analysis.
- Define rigorous grading criteria covering numerical accuracy, convergence, complexity, feasibility, and mathematical correctness.
- Establish appropriate numerical tolerances, stopping criteria, stability requirements, and reproducibility controls.
- Develop automated tests that validate results across edge cases and alternative valid implementations.
- Debug issues involving floating-point precision, solver failures, conditioning, convergence, and performance.
- Document mathematical formulations, assumptions, expected outputs, and known limitations.
Requirements:
- Advanced academic or professional expertise in Mathematics, Applied Mathematics, Statistics, Computational Mathematics, or a closely related quantitative discipline.
- Strong programming skills in Python, R, Julia, C/C++, Bash, or another relevant scientific programming language.
- Hands-on experience with numerical analysis, optimization, statistics, mathematical modeling, or computational mathematics.
- Experience implementing and validating mathematical algorithms or computational models.
- Ability to work independently in Linux or terminal-based environments.
- Strong understanding of numerical precision, convergence, stability, and mathematical correctness.
- Experience developing, debugging, and validating reproducible computational workflows.
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