$70-$180/hr biology and life sciences work, on your schedule
Review AI-generated experimental designs, analyses, and life-sciences claims the way you'd review a labmate's protocol. Flag the missing control, the contamination risk, the conclusion the assay can't support. Bench-earned intuition for what actually works in the lab is exactly what AI labs need.
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Hi, we're Zac and Jack, the founders of Terac. We want to talk to you directly, because you are the most important part of what we're building.
Terac is a community of experts. People who have spent years getting good at something specific and hard. The world is about to need more of you, not less. As AI takes on more of the world's work, the bottleneck shifts to the people who actually know what they're talking about.
Expert labor is the rarest resource in the world right now, and it is shockingly hard to find. The companies that need a biologist's eye on a missing control spend weeks chasing people, paying placement fees, and settling for whoever is available. Meanwhile thousands of qualified people are sitting with knowledge that no one ever asks for.
That gap is what we're here to close. Every project that lands on Terac is routed to the people who actually know the answer, on their schedule, paid fairly, and only when the work is verified. No middleman taking a cut of your time. No vague gigs. No chasing checks.
We care about every single person in this community. If you join Terac, you're not a row in a database to us. We read the feedback. We answer the emails. We will fight for you when a customer is being unreasonable, and we will be honest with you when something on our side is broken. The quality of this panel is our entire company, and we owe you a serious bar.
If you've made it this far, here is what we're asking: claim your profile. Put your expertise on the record. Let the world's most ambitious teams come find you for the work only you can do.
Biology & Life Sciences questions
Still curious? Write to us at support@terac.com.
Yes. Computational and bioinformatics backgrounds are actively sought, particularly for tasks involving RNA-seq differential expression pipelines, single-cell analysis (Seurat, Scanpy), variant calling, or statistical modeling of omics data. If you can evaluate whether a DESeq2 or edgeR analysis was run correctly and whether the biological interpretation holds, that is exactly the kind of domain-specific judgment the work requires.
Tasks vary by sub-domain but typically include: reviewing AI-generated experimental protocols for controls and assay validity, annotating AI-written mechanistic claims in signaling pathways or pharmacology, creating worked examples that show expert reasoning through a Western blot or flow cytometry result, and scoring AI summaries of published studies for accuracy against the source paper. You will not be conducting lab work or writing original research; you are evaluating and teaching from your existing knowledge.
Regulatory and compliance expertise is a distinct, high-value category. Tasks in this area include reviewing AI-generated IND or BLA sections for correct application of FDA 21 CFR Part 11, ICH E6(R2) GCP guidelines, or GLP study design requirements. If you can identify where an AI has mischaracterized nonclinical safety study expectations or misapplied GMP documentation standards, that judgment is directly applicable.
Tasks involving select agents listed under 42 CFR Part 73 or dual-use research of concern (DURC) as defined under federal oversight policy are flagged separately and routed only to reviewers with the appropriate background and institutional standing. General participation does not require any biosafety authorization, and you will not encounter that content unless you have explicitly opted into a restricted category and your credentials have been verified for it.
Industry experience is treated as equivalent and in some categories is preferred. Translational biology, process development, CMC regulatory work, biomarker strategy, and ADMET evaluation are areas where industrial scientists have daily hands-on exposure that academic training alone does not replicate. The screening process evaluates your ability to critique domain-specific content at a professional level, not whether that experience was earned in a company or a university lab.
Why your expertise matters
Biology and life sciences span enormously complex, interconnected systems where a model's plausible-sounding error - a misattributed mechanism of action, a misapplied statistical model for gene expression data, or a conflated regulatory pathway - can mislead downstream research or product decisions in ways that are hard to detect without domain fluency. Frontier AI models are increasingly used to summarize literature, design experiments, interpret assay results, and assist with regulatory submissions, meaning errors in biological reasoning carry real consequences. Your ability to distinguish a valid experimental inference from a confounded one, or to recognize when a model has hallucinated a citation to a non-existent clinical study, is exactly what makes expert review irreplaceable.
How pay works
Pay within the $70-180/hr band reflects the depth and specificity of your sub-domain expertise: a molecular biologist with hands-on CRISPR screening experience or an expert in FDA 21 CFR Part 11 compliance will consistently place higher than a generalist, as will researchers who can evaluate statistical modeling choices in omics data or critique mechanistic pharmacology arguments at publication level. All work is fully remote, tracked hourly or by verified deliverable, and paid only on confirmed completion - there are no retainers and no speculative unpaid rounds.
What the work looks like
A sample of the biology and life sciences work you would pick up. Every project is scoped, remote, and paid on verified completion.
- Review an AI-generated experimental protocol for a CRISPR knock-in experiment and identify steps where off-target effects are inadequately controlled or where guide RNA design logic is flawed.
- Evaluate a model-produced summary of a Phase II clinical trial and flag any mischaracterization of primary endpoints, patient stratification criteria, or adverse event reporting standards.
- Annotate a set of AI-generated gene expression analysis writeups, marking claims where the model incorrectly applied differential expression statistics or conflated biological replicates with technical replicates.
- Create a worked example of mechanistic reasoning for a signaling pathway, walking through how an expert interprets a Western blot result in the context of downstream pathway crosstalk.
- Assess an AI-written regulatory biology section of an IND application and correct any misapplication of FDA guidance on nonclinical safety studies or GLP compliance language.
- Score a batch of AI responses to ecology modeling questions, distinguishing correct population genetics inference from plausible-sounding but statistically invalid conclusions.
Specialties we match
Biology & Life Sciences projects span a wide range of focus areas. Tell us where you go deep and we route the work that fits.
- CRISPR/Cas9 and gene editing
- Flow cytometry and cell sorting
- Next-generation sequencing (NGS) analysis
- Protein structure and function
- Pharmacokinetics and ADMET modeling
- Regulatory biology (FDA, EMA, GLP/GMP)
- Bioinformatics and R/Python pipelines
- Cell culture and in vitro assay design
- Clinical trial biology and biomarkers
- Ecology and population dynamics
- Synthetic biology and metabolic engineering
- Immunology and antibody development
