Computational Bayesian Problem Designer

Obsidian; Greater London; Remote; GBP 50,000 - 80,000; Part time

Job summary

Obsidian is seeking a Computational Bayesian Statistics and Applied Mathematics Expert in Greater London. The role involves designing challenging computational problems that assess advanced AI systems against scientific workflows.

The ideal candidate will have graduate-level expertise and proven proficiency with relevant scientific software. A strong background in Python and independent problem design skills are essential for this position.

Qualifications

• Graduate-level expertise (MS or PhD preferred) in computational Bayesian statistics and applied mathematics.
• Proficiency with scientific software libraries demonstrated through publications or contributions.
• Strong Python skills for writing problem setups and validators.

Responsibilities

• Design challenging computational problems for AI to test scientific software capabilities.
• Refine problems through testing with AI models to achieve target difficulty.
• Prepare problems that require strategic thinking and analysis for AI.

Skills

Computational Bayesian Statistics

Applied Mathematics

Python programming

MCMC

Education

Graduate-level training in a relevant STEM field (MS, PhD, or equivalent)

Tools

PyMC

PyStan

scikit-fem

Job description

Obsidian is seeking a Computational Bayesian Statistics and Applied Mathematics Expert in Greater London. The role involves designing challenging computational problems that assess advanced AI systems against scientific workflows.

The ideal candidate will have graduate-level expertise and proven proficiency with relevant scientific software. A strong background in Python and independent problem design skills are essential for this position.