Genetics AI Problem Designer (Remote, Part-Time)

Anyone AI; Buenos Aires; A distancia; ARS 52.108.000 - 83.372.000; A tiempo parcial

Descripción de la vacante

Anyone AI is seeking experts in Genetics to design rigorous, deterministic, single-answer problems for AI training and evaluation. The role emphasizes exact solutions with complete verified reasoning and documentation, spanning Mendelian to population genetics and incorporating genomic data.

Ideal candidates hold a Master’s or PhD in genetics-related fields, have strong quantitative and writing skills, and can use Python or R to validate conclusions.

Formación

• Master’s or PhD in Genetics, Genomics, Molecular Biology, Computational Biology, or closely related field.
• Strong research or industry experience involving genetics, genomics, molecular biology, or quantitative genetic analysis.
• Excellent quantitative reasoning and data-analysis skills.
• Solid understanding of inheritance, genetic variation, experimental design, probability, and statistical genetics.

Responsabilidades

• Design advanced genetics problems for frontier AI training and evaluation.
• Create deterministic problems with exactly one correct answer.
• Write complete, verified solutions and document the reasoning process.
• Develop problems involving Mendelian, population, molecular, quantitative genetics, genomics, or genetic variation.
• Create problems requiring multi-step interpretation of inheritance patterns, data, pedigrees, or genomic information.
• Use Python, R, or genetics-specific tools to validate solutions when relevant.
• Ensure outputs are technically precise, reproducible, and well-written in English.

Conocimientos

Genetics

Quantitative reasoning

Data analysis

Technical writing

Educación

Master’s or PhD in Genetics/Genomics

Herramientas

Python

R

PLINK

GATK

Descripción del empleo

Anyone AI is seeking experts in Genetics to design rigorous, deterministic, single-answer problems for AI training and evaluation. The role emphasizes exact solutions with complete verified reasoning and documentation, spanning Mendelian to population genetics and incorporating genomic data.

Ideal candidates hold a Master’s or PhD in genetics-related fields, have strong quantitative and writing skills, and can use Python or R to validate conclusions.