Computational Mathematician - Fully Remote

Mercor; Berlin; Hybrid; EUR 60.000 - 90.000; Vollzeit

Benefits dieser Stelle

Publications in peer-reviewed journals

Prior scientific software or research

Zusammenfassung

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code) and to partner with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

The role requires depth in at least two subdomains (numerical linear algebra, computational mechanics, computational finance) and working proficiency in Python or R for scientific computing, plus comfort with Git/GitHub and Docker in a

Qualifikationen

• PhD in mathematics or closely related field.
• Depth in at least two subdomains listed (numerical linear algebra, computational mechanics, computational finance).
• Proficiency in Python or R for scientific computing.
• Comfort with Git/GitHub and running code in Docker with PR-based workflows.

Aufgaben

• Source your own material: published paper, Kaggle dataset, open-source repo, or self-designed scenario.
• Write scientific prompts based on the input.
• Build grading criteria that define a correct answer.
• Calibrate against frontier models so that a task ships when models struggle.

Kenntnisse

Numerical linear algebra

Computational mechanics

Computational finance

Python

R

Git & GitHub

Docker

Ausbildung

PhD in Mathematics / Applied Mathematics / Computational Mathematics

Jobbeschreibung

Mercor is hiring PhD and Master's scientists to author AI evaluation tasks (Sci Code)

Mercor is partnering with leading AI labs on a new benchmark for scientific computing. You will author original, executable research problems that today's frontier models cannot solve.

Domains - depth required in at least two subdomains (with a coding focus)

• Mathematics — numerical linear algebra, computational mechanics, computational finance

What you'll do

• Source your own material: a published paper, a Kaggle dataset, an open-source repository, or a scenario you design

• Write scientific prompts based on the input

• Build the grading criteria that define a correct answer

• Calibrate against frontier models — a task ships only when strong models fail it more often than they succeed

Required

• PhD in mathematics, applied mathematics, computational mathematics, or a closely related field

• Demonstrated depth in at least two of the following subdomains: numerical linear algebra, computational mechanics, computational finance

• Working proficiency in Python or R for scientific computing

• Comfortable with Git/GitHub and running code in Docker — authoring runs through a pull-request workflow with automated quality checks

Preferred

• Publications in peer-reviewed journals

• Prior scientific software or research engineering experience

Engagement

• Duration: 6 weeks

• Commitment: part-time, 20+ hours per week

• Start date: immediate

Process

1. A 25-minute conversational interview covering your background, experience, and motivations

2. Follow up within a few days with next steps and onboarding