TuringDomain experts
Scientific Computing Expert: Mathematics PHD - $300/Approved Task
$300/task
About this role, in Turing's words
We are seeking Mathematics experts to develop realistic, terminal-based scientific tasks for Terminal Bench Science. You will design tasks involving numerical analysis, optimization, statistics, mathematical modeling, probability, dynamical systems, and computational mathematics. The role focuses on evaluating whether AI agents can formulate mathematical problems, implement reliable algorithms, operate in a terminal environment, debug numerical workflows, and produce verifiable computational results.
What you'll do
- Design and build authentic computational mathematics tasks — translate mathematical and research workflows into self-contained, multi-step terminal environments, complete with datasets, equations, model definitions, constraints, and expected outputs.
- Implement expert solutions using Python, R, Julia, C/C++, Bash, or other relevant tools, covering areas such as optimization, numerical integration, differential equations, matrix computation, statistical inference, stochastic modeling, or algorithm analysis.
- Define rigorous grading criteria, including numerical accuracy, convergence, complexity, feasibility, and mathematical correctness, along with appropriate tolerances, stopping criteria, stability requirements, and reproducibility controls.
Show all 5 itemsHide the other 2 in What you'll do
- Develop automated tests and debug issues — validate results across edge cases and alternative valid implementations, and troubleshoot problems involving floating-point precision, solver failures, conditioning, convergence, and performance.
- Document the work thoroughly, including assumptions, mathematical formulations, expected outputs, and known limitations.
Candidate background
What We're Looking For
- Ph.D., postdoctoral experience, or equivalent advanced technical experience in mathematics, statistics, or a closely related discipline.
- Strong programming skills in Python, R, Julia, C/C++, Bash, or another relevant language.
- Experience working in Linux or terminal-based environments.
- Experience with numerical methods, optimization, statistics, mathematical modeling, or scientific computation.
- Ability to independently implement, test, and validate computational algorithms.
Quoted from selected sections of Turing's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Turing's words
Posted by Turing, reproduced here so you can judge the role before clicking. Original posting ↗
About Turing Turing is one of the world's leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent.
Engagement Details
• Commitments Required: At least 6 hours per day and a minimum of 40 hours per week, with a 4-hour overlap with PST.
• Employment Type: Contractor assignment (no medical/paid leave)
• Duration of Contract: 5 weeks (expected start date is next week)
• Payment Type: Pay per task — $300 per approved task
About the Role We are seeking Mathematics experts to develop realistic, terminal-based scientific tasks for Terminal Bench Science. You will design tasks involving numerical analysis, optimization, statistics, mathematical modeling, probability, dynamical systems, and computational mathematics. The role focuses on evaluating whether AI agents can formulate mathematical problems, implement reliable algorithms, operate in a terminal environment, debug numerical workflows, and produce verifiable computational results.
What You'll Do
• Design and build authentic computational mathematics tasks — translate mathematical and research workflows into self-contained, multi-step terminal environments, complete with datasets, equations, model definitions, constraints, and expected outputs.
• Implement expert solutions using Python, R, Julia, C/C++, Bash, or other relevant tools, covering areas such as optimization, numerical integration, differential equations, matrix computation, statistical inference, stochastic modeling, or algorithm analysis.
• Define rigorous grading criteria, including numerical accuracy, convergence, complexity, feasibility, and mathematical correctness, along with appropriate tolerances, stopping criteria, stability requirements, and reproducibility controls.
• Develop automated tests and debug issues — validate results across edge cases and alternative valid implementations, and troubleshoot problems involving floating-point precision, solver failures, conditioning, convergence, and performance.
• Document the work thoroughly, including assumptions, mathematical formulations, expected outputs, and known limitations.
What We're Looking For
• Ph.D., postdoctoral experience, or equivalent advanced technical experience in mathematics, statistics, or a closely related discipline.
• Strong programming skills in Python, R, Julia, C/C++, Bash, or another relevant language.
• Experience working in Linux or terminal-based environments.
• Experience with numerical methods, optimization, statistics, mathematical modeling, or scientific computation.
• Ability to independently implement, test, and validate computational algorithms.
Working with TuringPay, getting started and work, from Turing's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Paid monthly, around the 5th, straight to your bank account, or inside Deel on projects run through Deel. Its help articles disagree on whether that is the 5th calendar day or business day. help.turing.com/articles/9691407757-project-onboarding, help.turing.com/articles/6582454854-what-if-i-haven-t-rec..., help.turing.com/articles/1226770947-project-offboarding
- Before your first paid task
- A short application, with tests on some roles. Turing's review article says an interview is typically required for all roles. Onboarding covers the terms, ID verification with a driver's license or passport, and tax and payment details. help.turing.com/articles/2020987592-apply-for-jobs-at-turing, help.turing.com/articles/9179629201-how-long-does-the-app..., help.turing.com/articles/9691407757-project-onboarding
- How much work
- Review takes from 48 hours to 6 weeks after you finish applying, and the client makes the final choice. No reply within 6 weeks usually means you were not selected. help.turing.com/articles/9179629201-how-long-does-the-app..., help.turing.com/articles/2020987592-apply-for-jobs-at-turing
- Contract
- Depending on the project, the engagement rests on Turing's Terms of Service and a Service Agreement, on Deel, or on a partner that provides the contract. help.turing.com/articles/6582454854-what-if-i-haven-t-rec...
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Domain experts roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Turing's posting. How we count.
Pay across the field: Domain experts
Across 700 roles in this field with a stated hourly rate in US dollars, on 18 platforms, the middle half pays $65 to $130 an hour at the top of the range, and the median is $100.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 149 | $24 to $200 · median $80 |
| micro1 | 136 | $28 to $400 · median $110 |
| AfterQuery | 88 | $45 to $175 · median $100 |
| Handshake AI | 79 | $30 to $300 · median $85 |
| Mercor | 78 | $55 to $450 · median $120 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 25 Sep 2026, and still on Turing's list when we last read it on 13 Oct 2026.
- Posted by Turing
- First seen by AIPayList
- Last seen live
- Listing ID
- 108940
Pay as the source states it: “Payment Type: Pay per task — $300 per approved task”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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