Mathematics PhD - AI Evaluation Expert

Mercor; Berlin; Vor Ort; EUR 34.000 - 48.000; Teilzeit

Zusammenfassung

Mercor is seeking PhD and Master's level scientists to author AI evaluation tasks (Sci Code) and contribute to a new benchmark for scientific computing. You will create original, executable research problems that frontier models cannot solve, with a focus on two deep subdomains and a strong emphasis on Python-based analysis. This 6-week, part-time role starts immediately and centers on crafting prompts and grading criteria.

Qualifikationen

• PhD in mathematics, applied mathematics, computational mathematics or closely related field.
• Depth in at least two of: numerical linear algebra, computational mechanics, computational finance.
• Proficiency in Python for scientific computing.
• Comfortable with Git/GitHub and running code in Docker, authoring runs through a PR workflow with automated quality checks.

Aufgaben

• 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

Kenntnisse

Analytical reasoning

Technical writing

Ausbildung

PhD in mathematics, applied mathematics, computational mathematics

Tools

Git/GitHub

Docker

Python for scientific computing

Pull-request workflow

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 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