Biology AI Challenge Designer - Remote, Part-Time

Anyone AI Inc.; United States; Teletrabalho; USD 39 000 - 55 000; Tempo parcial

Resumo da oferta

Anyone AI Inc. is seeking biology experts to design high-quality, deterministic AI training problems across molecular biology, genetics, systems biology, and computational biology.

You will use Python and bioinformatics tools to craft tasks with a single verifiable answer, submitting fully verified solutions from a remote, 20-hour-per-week engagement lasting two months with potential extension. The role emphasizes rigorous problem design grounded in real biological practice and clear written

Qualificações

• Master's or PhD in Biology or related life sciences.
• Experience with computational or quantitative biological analysis.
• Strong Python skills; data analysis or bioinformatics workflows preferred.
• Clear written English and strong attention to detail.

Responsabilidades

• Design advanced biology problems that challenge frontier AI systems.
• Create deterministic tasks with one correct answer.
• Submit complete, verified solutions.
• Build problems involving experimental reasoning, biological systems, computational analysis, or bioinformatics workflows.
• Use Python and, when relevant, specialized biology or bioinformatics tools.
• Ensure high standards of rigor, reproducibility, and technical clarity.

Conhecimentos

Python

Data analysis

Bioinformatics workflows

Analytical reasoning

Formação académica

Master's or PhD in Biology

Ferramentas

Bioconductor

Genomics workflows

Structural biology tools

Descrição da oferta de emprego

Anyone AI Inc. is seeking biology experts to design high-quality, deterministic AI training problems across molecular biology, genetics, systems biology, and computational biology.

You will use Python and bioinformatics tools to craft tasks with a single verifiable answer, submitting fully verified solutions from a remote, 20-hour-per-week engagement lasting two months with potential extension. The role emphasizes rigorous problem design grounded in real biological practice and clear written