Life Sciences Scientific Reasoning Task Designer

About OpenTrain
OpenTrain is the centralized, open platform where AI training and data-labeling freelancers find work, consolidate opportunities across platforms, and build a unified AI training portfolio they control. We make specialized AI training work easier to track, apply for, and grow into a durable freelance career.

About this role
OpenTrain is recruiting for a Life Sciences Scientific Reasoning Task Designer to create advanced, non-coding scientific tasks for AI training and evaluation. You will turn realistic biological research scenarios, experimental results, figures, sequences, structures, datasets, and literature-style evidence into challenging problems that test synthesis and interpretation rather than factual recall. The work calls for objectively defensible questions, rigorous reference answers, and careful review of claims, assumptions, calculations, and conclusions.

What you will do
Design novel, graduate-level life sciences problems grounded in realistic research contexts. Create clear, self-contained questions and scientifically defensible reference answers. Interpret experiments, datasets, figures, sequences, structures, and other biological evidence. Validate biological claims, calculations, assumptions, and conclusions. Identify ambiguity, alternative interpretations, and insufficiently constrained questions. Document tasks clearly, maintain reproducibility where applicable, and incorporate reviewer feedback while maintaining quality and throughput.

Required skills
You should have a Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences, along with strong expertise in at least one biological discipline. The role requires demonstrated ability to interpret scientific experiments, data, and research findings, as well as strong scientific writing skills and close attention to precision. You should be able to reason through complex evidence and communicate conclusions clearly.

Helpful background
Experience designing graduate-level problems, assessments, or research exercises is valuable. Background reviewing scientific manuscripts, translating complex scientific concepts into precise self-contained questions, evaluating AI-generated scientific responses, working with AI or machine-learning evaluation datasets, publishing peer-reviewed research, or teaching and mentoring at the graduate level is also relevant.

Engagement details
This is a remote contractor assignment for a freelancer focused on scientific reasoning and task creation rather than programming or executing code. The engagement lasts one month and requires at least 40 hours per week, including 4 hours of overlap with Pacific Time.

Why work with OpenTrain
OpenTrain gives freelancers one place to manage AI training opportunities instead of rebuilding proof of work on every platform. A stronger OpenTrain profile helps you show credible experience, discover roles that match your skills, and turn AI training and data-labeling work into a long-term portfolio.