Life Sciences Specialist - Remote
• *About The Job • *Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include • *Benchmark** , • *General Catalyst** , • *Peter Thiel** , • *Adam D'Angelo** , • *Larry Summers** , and • *Jack Dorsey** . • *Position:** PhD-Level Life Scientist • *Type: • *Contract • Compensation: • $80–$125/hour • *Location: • *Remote • *Commitment: • *High touch and high excellence required • *Role Responsibilities • Create challenges related to molecular biology, genomics, transcriptomics, epigenetics, and proteomics with scientific accuracy and depth. • Design experimental challenges, evaluating controls, confounders, reproducibility, and data interpretation. • Develop 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 • *Must-Have • 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. • *Application Process (Takes 20–30 mins to complete) • Upload resume • AI interview based on your resume • Submit form • Resources & Support • For details about the interview process and platform information, please check: • For any help or support, reach out to: [email protected] • PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity. ,