Stellenbeschreibung
Role Overview
Mercor is seeking PhD-level life scientists with deep expertise across biology, omics, and computation to support a research project with a leading AI lab. In this role, you will leverage your domain knowledge in biology to create challenges for leading AI models - ensuring scientific accuracy, experimental rigor, and sound reasoning across complex biological questions. Your hands-on research experience will directly shape how next-generation AI systems understand and reason about the life sciences.
Key Responsibilities
- Create challenges related to molecular biology, genomics, transcriptomics, epigenetics, and/or proteomics with scientific accuracy and depth
- Design experimental challenges, including evaluation of controls, confounders, reproducibility, and data interpretation
- Create high-quality training data including research-level questions, answers, and evaluation rubrics across domains
- Provide structured feedback on challenges covering wet-lab protocols, computational analysis pipelines, and study design
- Apply quantitative and bioinformatics reasoning to calibrate model performance on complex, multi-step biological problems
Qualifications
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 - e.g., faculty, staff scientist, research scientist, or postdoc with an active institutional affiliation and ongoing research
- Hands-on wet-lab experience - must have designed and executed experiments (not purely computational)
- Strong experimental design and scientific reasoning - demonstrated expertise with 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 - 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 - experience in computational biology, bioinformatics, statistical genetics, and/or machine learning for omics (analysis, interpretation, and study design support)
- Breadth across molecular modalities:
- DNA / RNA / protein biology; gene expression and translation
- Protein assays (e.g., Western blot, ELISA, mass spectrometry-based proteomics)
- Small molecules / chemical biology exposure
Job Details
- Pilot program to start. High touch and high excellence required - with potential for extension based on performance.
