Computational Biology Expert (PhD)

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.