Computational Life Sciences AI Task Designer

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the leading platform for finding and building careers in AI training and data labeling, helping specialists discover projects, build a professional profile, and apply in minutes.

Creating an OpenTrain account is free, and your profile can help you present credible experience across a growing field of AI training work.

• Worldwide contract opportunity
• Part-time engagement requiring 20+ hours per week
• English-language work

About AI Training Work

AI training is the human side of building artificial intelligence. Experts create, review, and evaluate examples that help AI systems reason, follow instructions, and perform specialized work more reliably.

In this role, your scientific judgment and programming expertise will help assess whether AI agents can complete authentic computational life sciences workflows rather than simply recall information.

• Work directly on cutting-edge AI evaluation
• Apply specialized research knowledge to practical model testing
• Help shape how AI systems perform scientific analysis

The Role

OpenTrain AI is seeking a Computational Life Sciences AI Task Designer to create realistic, multi-step scientific workflows for evaluating AI agents. You will translate research practices into self-contained tasks containing scientific data, executable code, expected deliverables, reproducible solutions, and objectively verifiable evaluation criteria.

The work combines life sciences expertise, scientific programming, experimental judgment, and careful validation of agent outputs. The role is classified as entry level in the project data, while the required qualifications call for Ph.D.-, postdoctoral-, or equivalent-level research expertise.

• Subject area: Computational Life Sciences AI Evaluation
• Work type: Contractor and part time
• Time requirement: 20+ hours per week
• Work location: Worldwide

What You'll Do

You will design challenging agentic workflows across the life sciences that require data inspection, method selection, code execution, troubleshooting, analysis, and synthesis. Tasks should reflect authentic computational research while remaining bounded, reproducible, and objectively gradable.

You will also validate the scientific and technical integrity of each task, package the necessary resources, and refine work based on reviewer feedback.

• Create realistic scientific datasets, input files, instructions, constraints, and expected deliverables
• Develop expert solutions, ground truths, and automated or semi-automated grading criteria
• Run evaluations reproducibly in network-isolated computational sandboxes
• Validate scientific assumptions, calculations, code, intermediate outputs, and final answers
• Package dependencies, data, and computational resources reliably
• Maintain task quality and respond to reviewer feedback

Required Qualifications

This role requires advanced life sciences research expertise at the Ph.D., postdoctoral, or equivalent level. You should be comfortable independently assessing both scientific reasoning and computational results.

Strong Python and scientific programming experience are essential, along with experience performing multi-step computational scientific analyses. You must also be able to turn authentic research workflows into bounded tasks with objective evaluation criteria.

• Ph.D., postdoctoral, or equivalent research experience in the life sciences
• Strong Python and scientific programming skills
• Experience designing or executing multi-step computational scientific analyses
• Ability to validate scientific assumptions, calculations, code, and computational outputs
• Ability to create reproducible workflows and objectively gradable evaluation criteria

Helpful Background

Experience in computational or data-intensive life sciences can support success in this role. Familiarity with reproducible research infrastructure and AI evaluation environments is also valuable.

• Bioinformatics or computational genomics
• Systems biology or computational neuroscience
• Biostatistics or computational drug discovery
• Computational biochemistry, structural biology, or protein engineering
• Computational microbiology
• Scientific libraries, command-line tools, or reproducible research pipelines
• AI agents, automated evaluation environments, Docker, or Linux
• Computational and data-intensive life sciences publications

Why Build Your AI Training Career With OpenTrain

AI training and data-labeling work is a fast-growing way to contribute to technology while using specialized knowledge. OpenTrain gives you a place to build a durable portfolio of AI training experience and find projects aligned with your capabilities.

For computational life sciences researchers, this work offers an opportunity to bring real scientific standards to the development and evaluation of advanced AI systems.

• Build a profile that showcases specialized AI training experience
• Discover projects that match your research and technical skills
• Develop a long-term portfolio in an expanding AI industry
• Apply through a free OpenTrain account