Posted by: micro1 Openings: 30 Compensation: $40 – $60/hr Job Type: Contractor Location: Remote
Required Skills: Python, Bash
Job Summary
In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
Key Responsibilities
- Leverage your biology domain expertise to evaluate, annotate, and benchmark AI systems in real-world computational biology use cases.
- Assess the accuracy, relevance, and performance of AI-generated outputs in genomics, transcriptomics, and systems biology scenarios.
- Apply advanced analytical reasoning to critically review scientific workflows and pipelines, identifying strengths and areas for improvement.
- Collaborate with interdisciplinary teams, providing feedback on AI model performance based on biological context.
- Document observations and findings with clarity, highlighting scientific rationale and actionable insights.
- Communicate complex concepts effectively through both written and verbal channels to technical and non-technical stakeholders.
- Stay current on emerging trends in computational biology, bioinformatics, and machine learning in biology.
Required Skills and Qualifications
- PhD in Biology, Bioinformatics, or a closely related field, or equivalent industry/research experience.
- Proven experience in data-driven biological research and computational analysis workflows.
- Proficiency with scripting (Python, R, Bash) and scientific tools such as BWA, GATK, STAR, Salmon, Seurat, or Scanpy would be ideal.
- Deep understanding of genomics, transcriptomics, structural biology, or systems biology is desirable.
- Excellent scientific reasoning, analytical, and problem-solving abilities.
- Strong written and verbal communication skills, with the ability to articulate findings and collaborate effectively.
- Comfort working remotely and contributing to distributed teams.
Preferred Qualifications
- Experience with AI/ML or LLM evaluation in a biology context.
- Hands-on experience with NGS pipelines, CRISPR workflows, AlphaFold, or PyMOL.
- Published research or contributions to open-source projects in computational biology or bioinformatics.