Scientific Computing Expert (Life Sciences)

The work

You will design realistic, multi-step computational life sciences tasks used to evaluate AI agents. Each task must require scientific data inspection, method selection, code execution, troubleshooting, analysis, and synthesis.

You will build the materials needed to run and assess each task in a controlled, network-isolated environment. This includes input files, datasets, instructions, constraints, expected deliverables, reproducible expert solutions, ground truths, and objective grading criteria.

• Create workflows in areas such as bioinformatics, computational genomics, systems biology, biostatistics, computational drug discovery, structural biology, protein engineering, and computational microbiology.
• Check scientific assumptions, calculations, code, intermediate outputs, and final answers.
• Make sure tasks are self-contained, executable, and supported by clear evaluation standards.

What it pays and takes

This is a remote contractor assignment with a five-week engagement. The listing calls for 20 or more hours per week and includes a four-hour overlap with Pacific Time.

• Pay: $300 per approved task.
• Work arrangement: Remote contractor assignment.
• Engagement length: 5 weeks.
• Availability: 20 or more hours per week, including a four-hour Pacific Time overlap.
• Education or experience: Ph.D., postdoctoral appointment, or equivalent research experience in the life sciences.
• Technical skills: Strong computational and scientific programming experience, especially in Python.
• Analysis skills: Experience with multi-step computational scientific analyses and independently validating scientific reasoning and computational outputs.
• Language: Professional fluency in English.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work is the human side of building artificial intelligence. People create examples, review model outputs, and develop evaluation tasks so AI systems can produce more accurate and useful results. Experienced specialists are needed when the work depends on advanced scientific knowledge and careful technical judgment.