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Experimental Biologist

DataAnnotation · 100% remote · Contract · Posted

Pay
$40–125/hr
Location
North America, Europe and Oceania
Languages
English
Hours
Flexible hours
Openings
Not listed
Level
Expert
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Summary

Design experimental biology tasks and evaluate AI results against laboratory standards. Write grading rubrics and identify errors using raw data and experimental evidence.

What you'll do

  • Design experimental tasks with prompts and supporting laboratory files.
  • Grade AI experimental plans, quality control summaries, and troubleshooting reports.
  • Write grading rubrics and explain assessment decisions.
  • Identify ignored controls, incorrect normalization, missed outliers, and fabricated data.

Requirements

  • At least 3 years designing and running laboratory experiments after undergraduate study.
  • Specialized knowledge in at least one listed experimental biology field.
  • Hands-on experience designing experiments and diagnosing failed runs.
  • Ability to generate and check primary data using raw instrument output.
  • Master's degree, PhD, or current PhD candidacy in biology or a related field.
  • Specified graduate education completed in the United States, Canada, Europe, or the United Kingdom.
  • Clear written English, comfort with ambiguity, and familiarity with AI tools.
  • Based in the United States, Canada, or the United Kingdom; Ireland and Australia may also be accepted.

Skills

  • Molecular Biology
  • Cloning
  • Cell Culture
  • Protein Biochemistry
  • Immunology
  • Flow Cytometry
  • Imaging and Histology
  • Experimental Troubleshooting

Full description

Overview

We’re looking for experienced bench scientists to help train AI models. You’ll design realistic experimental-biology tasks from your own practice, run them through frontier AI systems, and grade what comes back against the standard you’d hold a colleague to.

The models can already talk fluently about biology. What they can’t yet do reliably is the real work: call a plate QC go/no-go, gate a flow panel, check a cloning strategy, or read a Western blot from the raw images. Your bench judgment becomes the benchmark those models are measured against.

What you’ll actually do

  • Design realistic experimental tasks from your own workflows: the scenario, the prompt, and the supporting files an agent would need (plate maps and reader output, gel and blot images, flow summaries, protocols, QC records).
  • Run tasks through frontier AI agents and grade the deliverable they produce (a QC summary, experimental plan, or troubleshooting memo) against a professional standard.
  • Write clear grading rubrics that specify what a correct deliverable must contain (the right controls, the right wells excluded, the right diagnosis of a failed run), and explain why a response passes or fails.
  • Flag concrete failures with evidence: controls ignored, edge effects and outliers missed, wrong normalization, plausible-sounding troubleshooting the raw data contradict, or fabricated values.

Problems draw on whatever you know best:

  • Molecular and cell biology: cloning, cell culture, and cell-based assays.
  • Protein biochemistry: purification, characterization, and assay development.
  • Immunology and flow cytometry: panel design and gating.
  • Imaging and histology, microbiology and virology.
  • In vivo and preclinical work, plus lab operations and analytical sciences.

Roles this fits

Common backgrounds: Research Scientist, Molecular / Cell Biologist, Postdoctoral Fellow.

What we look for

  • 3+ years designing and running experiments in a pharma, biotech, or academic research lab (counted after undergraduate study).
  • Depth in at least one of: molecular biology and cloning; cell culture and cell-based assays; protein biochemistry; immunology and flow cytometry; imaging and histology; microbiology or virology; in vivo and preclinical work.
  • A hands-on practitioner who designs and troubleshoots experiments, not only executes SOPs: you can explain what each control is for and diagnose why a run failed.
  • You generate and QC primary data, and can judge from raw instrument output whether a run is usable.
  • Master’s or PhD (or current PhD candidate) in biology or a related field, completed in the U.S., Canada, Europe, or the UK.
  • Clear written English, comfort with ambiguity, and familiarity with AI/LLM tools like Claude or ChatGPT.
  • Based in the United States, Canada, or the UK (Ireland and Australia may also be accepted).

Compensation

Up to $40 – $125+/hr depending on task difficulty and specialization. Many contributors add $10k–$100k+ a year; some make it their full-time income.

Location: Remote. Hours: Flexible hours. Type: Independent contractor. Payouts: Weekly.

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