Biomedical Scientist (PhD)

Job Summary: We are hiring experienced biomedical scientists, including research scientists, clinical laboratory scientists, postdoctoral researchers, and advanced doctoral candidates, for a contract project that tests whether frontier AI agents can carry out real experimental biology work. You will design research-grade tasks drawn from your own laboratory practice that a leading AI model cannot solve, then review how and why the model fails. We are especially interested in scientists with hands-on flow cytometry experience.

What you will do: Design self-contained tasks drawn from the practice of biomedical research, such as gating a multi-color flow cytometry dataset from raw FCS files, identifying the flaw in an experimental design, fitting and interpreting dose-response or enzyme kinetics data, performing quality control on a sequencing or mass spectrometry dataset, and reproducing a reported result and explaining a discrepancy. Assemble the materials each task needs, including data files, protocols, and context, write a reference solution, and define clear criteria or automated checks that determine whether a solution is correct. Because biological data is noisy and analysis involves judgment, criteria need to be precise or use well-justified tolerances. Run your task against a frontier AI agent, review its attempt with the same rigor you would apply to a manuscript under peer review, and refine the task until the failure reflects a real gap in the model's scientific capability rather than ambiguity or trick wording. Work with reviewers to bring each task to acceptance. Who we are looking forA PhD in biochemistry, cell biology, immunology, pharmacology, molecular biology, or a closely related field. Advanced doctoral candidates with substantial hands-on laboratory experience are also encouraged to apply. Hands-on experience in at least one of the following areas: flow cytometry and immunophenotyping, cell-based and phenotypic assays, biochemistry and protein science, mass spectrometry, genomics and bioinformatics, structural biology and molecular modeling, or drug metabolism, pharmacokinetics, and preclinical safety. Experience in research, clinical, or industry laboratory settings. Work in regulated environments, such as CAP or CLIA-accredited laboratories, counts fully toward this experience. For flow cytometry candidates: experience analyzing raw data yourself, ideally including FCS files and Flow Jo workspaces, rather than only overseeing analysis. Working knowledge of Python or R for data analysis. Familiarity with the command line and Git is a plus. Experience in assay development and validation, peer review, or designing course assignments and assessments is a strong advantage, because the work draws on the same skills. Why Cobalt AI:Advance frontier AI where it counts. Apply your scientific expertise to the data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through experimental problems. Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while deepening your understanding of how frontier models are trained and assessed. Work with a top-tier network. Collaborate with scientists from leading institutions, biotech companies, and clinical laboratories on high-impact, flexible work. Set your own schedule. Flexible 10 to 40 hour weeks that fit around your research position and your life. Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.