Clinical and Research Scientist (PhD)

Job Summary: We are hiring experienced clinical and research scientists, including clinical laboratory scientists, translational researchers, assay development scientists, postdoctoral researchers, and advanced doctoral candidates, for a contract project that tests whether frontier AI agents can carry out real work in clinical and translational science. 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 in clinical or research settings.

What you will do: Design self-contained tasks drawn from the practice of clinical and translational science, such as interpreting a multi-color immunophenotyping dataset from a hematologic oncology case, gating raw FCS files to identify an abnormal cell population, evaluating whether an assay validation meets its acceptance criteria, identifying the flaw in a translational study design, and reconciling a laboratory result that conflicts with the clinical picture. Assemble the materials each task needs, including data files, protocols, case context, and reference ranges, write a reference solution, and define clear criteria or automated checks that determine whether a solution is correct. Because laboratory data is noisy and interpretation 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 case sign-out or 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 for: A PhD in biochemistry, immunology, cell biology, molecular biology, pharmacology, clinical laboratory science, or a closely related field. Advanced doctoral candidates with substantial hands-on laboratory experience are also encouraged to apply. Hands-on experience in both clinical and research settings, such as work in a CAP or CLIA-accredited laboratory alongside academic, biotech, or pharmaceutical research. Hands-on experience in at least one of the following areas: clinical flow cytometry and immunophenotyping, assay development and validation, cell-based and immunological assays, clinical chemistry, molecular diagnostics, biomarker analysis, or translational research supporting therapeutic development. For flow cytometry candidates: experience analyzing raw data yourself, ideally including FCS files and Flow Jo or comparable analysis software, 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 validation, training or mentoring other scientists, 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 clinical and 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.