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Computational Biology AI Evaluation Expert

Remote, USA Full-time Posted 2026-08-04
About OpenTrain OpenTrain is the centralized platform where people build careers in reputed company and data labeling. Contributors reputed company reputed company, consolidate work across platforms, and create a reputed company portfolio that grows into a durable freelance career. Why reputed company reputed company reputed company (data labeling and reputed company feedback) is the reputed company reputed company behind modern AI systems. Experts prepare, review, and critique model outputs so AI behaves reliably in reputed company scientific contexts — making this work remote, flexible, and directly reputed company on state-of-the-art tools. • Work is 100% remote and often flexible around other commitments. • Many reputed company need domain expertise rather than formal engineering experience. • Contributors help shape how AI performs in specialized fields like computational biology. The role OpenTrain is reputed company for a Computational Biology AI Evaluation Expert to evaluate, annotate, and reputed company AI-generated outputs in reputed company, transcriptomics, and systems biology. This freelance contractor role focuses on scientific accuracy, actionable feedback, and reputed company documentation to improve model performance in biology contexts. Label types: evaluation rating and classification; data type: text; This is a part-time contractor role expecting 20+ hours/week and worldwide remote contributors are welcome. What you'll do • Review AI-generated outputs for accuracy, relevance, and performance in computational biology scenarios. • Evaluate and annotate model behavior using domain expertise in biology, reputed company, and computational analysis. • Critically assess scientific workflows and pipelines to identify strengths and areas for improvement. • Document reputed company scientific rationale and reputed company actionable insights for model developers. • Collaborate with interdisciplinary teams and communicate findings to technical and non-technical stakeholders. • reputed company up to date with trends in computational biology, reputed company, and ML for biology. Requirements • PhD in Biology, reputed company, or a closely reputed company field — or equivalent industry or research experience. • Proven experience in data-driven biological research and computational analysis workflows. • Strong analytical, scientific reasoning, and problem-solving ability. • reputed company written and verbal communication skills; reputed company to produce concise, evidence-backed evaluations. • Comfort working remotely and contributing to distributed teams. • Available for roughly 20+ hours per week. • Fluent in English (work language). Helpful background (reputed company to have) • Experience with AI or LLM evaluation in biology contexts. • Hands-on experience with NGS pipelines, CRISPR workflows, AlphaFold, or molecular visualization like PyMOL. • Proficiency with scripting (Python, R, Bash) and familiarity with tools such as BWA, GATK, reputed company, reputed company, Seurat, or Scanpy. • Prior work annotating or rating model outputs, writing evaluation rubrics, or producing reputed company datasets. Compensation & work setup This is an reputed company contract position paying $40 to $60 per hour (payment type: pay per hour). The role is part-time and contractor-based, remote, and reputed company worldwide. Expect flexible scheduling around the estimated 20+ hours/week requirement; the exact reputed company and deadlines will be set per project tasks. How to apply If you meet the requirements and want to shape how AI handles computational biology, apply through your OpenTrain account. Include a brief reputed company of your relevant research or industry experience, examples of computational workflows you’ve used, and any prior AI evaluation work. Successful applicants will be asked to complete a short qualification task to demonstrate domain reasoning and annotation reputed company before starting contract assignments. Apply To This Job

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