Role & responsibilities
Design authentic, multi-step computational mathematics tasks.
Translate mathematical and research workflows into self-contained terminal environments.
Prepare datasets, equations, model definitions, constraints, initial conditions, and expected outputs.
Implement expert solutions using Python, R, Julia, C/C++, Bash, or other relevant tools.
Create tasks involving optimization, numerical integration, differential equations, matrix computation, statistical inference, stochastic modeling, and algorithm analysis.
Define rigorous grading criteria based on numerical accuracy, convergence, complexity, feasibility, and mathematical correctness.
Establish appropriate tolerances, stopping criteria, stability requirements, and reproducibility controls.

Preferred candidate profile
Ph.D., postdoctoral experience, or equivalent advanced technical experience in Mathematics, Statistics, or a closely related discipline.




Solid expertise in applied mathematics, numerical analysis, optimization, statistics, probability, mathematical modeling, differential equations, dynamical systems, operations research, or computational geometry.
Strong programming skills in Python, R, Julia, C/C++, Bash, or another relevant programming language.
Experience working in Linux or terminal-based settings.
Experience with numerical methods, optimization, statistics, mathematical modeling, or scientific computation.
Ability to independently implement, test, and validate computational algorithms.
Solid understanding of numerical stability, error analysis, mathematical assumptions, and reproducibility.
Familiarity with NumPy, SciPy, SymPy, pandas, scikit-learn, JAX, PyTorch, CVXPY, or similar tools is preferred.

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