We’re looking for experienced computational biologists and bioinformaticians to help train AI models. You’ll design realistic analysis tasks from your own practice, run them through frontier AI systems, and grade what comes back against a professional standard. The models can talk fluently about biological data analysis.

QC an RNA-seq count matrix, prioritize variants, diagnose a batch effect, or audit a pipeline. Design realistic analysis tasks from your own workflows: the scenario, the prompt, and the files an agent would need (count matrices, sample sheets and metadata, VCFs, pipeline logs and QC output, analysis notebooks). Run tasks through frontier AI agents and grade the deliverable (an analysis report, annotated table, figure set, or notebook) against the standard you’d hold a colleague to.

Write clear grading rubrics (the right normalization, the right multiple-testing correction, the right biological reading) and explain why a response passes or fails.

Flag concrete failures with evidence: batch effects and confounders ignored, wrong statistical test or uncorrected p-values, misused reference version, silently dropped samples, or code that doesn’t do what the narrative claims.

Problems draw on whatever you know best:



Population and statistical genetics. Machine learning applied to biology.

Bioinformatics

Scientist, Genomics Data Scientist, Computational Biologist. 3+ years hands-on analyzing real biological data in industry, an academic lab, or a research institute (counted after undergraduate study). ~ You write, debug, and can explain your own analysis code in Python and/or R (at least one required, both preferred). ~ population and statistical genetics; ML applied to biology; You’ve owned a multistep analysis end to end, from raw or messy data to final interpretation, and can judge whether a result is real (normalization, batch effects, multiple-testing correction, biological interpretation). ~ Master’s or PhD (or current PhD candidate) in biology, bioinformatics, biostatistics, computer science, or a related field, completed in the U.Explicit written English, comfort with ambiguity, and familiarity with AI/LLM tools like Claude or ChatGPT. ~ some make it their full-time income. DataAnnotation is where 100k+ experts train the world’s leading AI models. $Flexible, remote, and always project-available. #

📌 Computational Public Health Researcher - AI Trainer (Quebec City)
🏢 DataAnnotation
📍 Quebec City