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Salary: USD 180,000 - 240,000 / annual
NewLimit is a biotechnology company developing medicines to treat age-related diseases by reprogramming the epigenome. The company uses functional genomics, pooled perturbation screening, and machine learning to understand epigenetic aging and disease.
You will lead NewLimit's Immunology team, which is developing reprogramming medicines to restore youthful function in aged T cells for treating inflammatory and infectious diseases, with emphasis on T cell and regulatory T cell (Treg) biology.
Key responsibilities:
- Lead a team of Scientists and Research Associates in developing reprogramming therapies
- Develop functional assays and pre-clinical models for inflammatory and infectious disease indications
- Evaluate reprogramming payloads using functional assays and pre-clinical models to validate payloads, select leads, and progress pre-clinical candidates
- Collaborate with Single Cell Technology, Epigenetic Editing, and Predictive Modeling teams to design, build, and test reprogramming interventions
- Contribute to product development decisions, company-wide goals, and technology platform development
- Contribute to day-to-day execution alongside your team (NewLimit operates on an "Everyone Executes" principle)
Requirements:
- Ph.D. in cell biology, immunology, or related field, OR comparable industry experience
- Proven experience leading a team and managing direct reports
- Experience with therapeutics development, ideally leading a portion of a discovery or development process in immunology, infectious disease, or inflammatory disease settings
- Deep knowledge of immunology and lymphocyte biology
Nice to have:
- Direct experience with T cell biology, including relevant functional assays, pre-clinical models, and experimental methods
- Experience with in vivo nucleic acid delivery technologies
- Experience with pooled screening and functional genomics methods
- Strong molecular biology foundations and experience designing transgenic constructs
- Experience with iterative product development cycles (design-build-test-learn)
- Knowledge of aging biology, computational biology, and machine learning
