This position offers an exciting opportunity for PhD-level life scientists to contribute to a cutting-edge research project in collaboration with a leading AI lab. You will utilize your extensive knowledge in biology to develop challenges for advanced AI models, ensuring scientific accuracy and experimental rigor while addressing complex biological questions. Your research expertise will play a crucial role in shaping the capabilities of next-generation AI systems in understanding life sciences.

• Create scientifically accurate challenges related to molecular biology, genomics, transcriptomics, epigenetics, and/or proteomics.
• Design experimental challenges that evaluate controls, confounders, reproducibility, and data interpretation.
• Generate high-quality training data, including research-level questions, answers, and evaluation rubrics across various domains.
• Provide structured feedback on challenges concerning wet-lab protocols, computational analysis pipelines, and study design.
• Apply quantitative and bioinformatics reasoning to assess model performance on complex, multi-step biological problems.

Required

• PhD (or MD/PhD) in a life-science field such as molecular biology, biochemistry, genetics, bioengineering, or systems biology.
• Currently or recently active in academia, such as faculty, staff scientist, research scientist, or postdoc with an active institutional affiliation and ongoing research.
• Hands-on wet-lab experience, having designed and executed experiments (not purely computational).
• Strong experimental design and scientific reasoning skills, with demonstrated expertise in controls, confounders, reproducibility, and interpretation.
• Bio-focused domain expertise in at least one of the following: Genomics, Transcriptomics, Epigenetics, Proteomics / protein assays / protein biochemistry.
• Evidence of research impact through published peer-reviewed work or influential preprints/tools/datasets with clear contributions (e.g., first/second author papers, senior-author leadership, or widely used methods and resources).

Preferred

• Computational and quantitative skills, with experience in computational biology, bioinformatics, statistical genetics, and/or machine learning for omics (analysis, interpretation, and study design support).
• Breadth across molecular modalities, including DNA/RNA/protein biology; gene expression and translation; protein assays (e.g., Western blot, ELISA, mass spectrometry-based proteomics); and exposure to small molecules/chemical biology.

This is an hourly position for a pilot program that requires high touch and high excellence, with the potential for extension based on performance.

The hourly compensation ranges from $80 to $125.

Applicants must have the necessary qualifications and experience as outlined above.