Senior / Principal Scientist, Cell Biology & Disease Modeling, Deep Science Lead

Lila Sciences•Cambridge, MA

1d•$148,000 - $208,000

About The Position

The Principal Scientist, Disease Modeling & Deep Biology will serve as the scientific authority for building, selecting, and deploying human disease models that enable discovery, mechanistic insight, and therapeutic decision-making across RNA, enzyme, antibody, and emerging modalities . This role is centered on disease modeling excellence , not any single technology. The successful candidate will bring breadth across biological systems and modalities , combined with deep hands-on expertise (>30% laboratory engagement) and the ability to lead projects and scientists from hypothesis through decision. The Principal Scientist will define disease-relevant experimental strategies—choosing the right model systems (cell lines, primary cells, iPSC-derived systems, organoids, co-cultures, in vitro or ex vivo platforms), the right perturbation approaches, and the right readouts to connect mechanism, phenotype, and therapeutic potential. This individual will operate as a scientific integrator - bridging deep biology, delivery, imaging, sequencing, and developability considerations into coherent, decision-enabling programs.

Requirements

PhD with 5-6+ years, or MS with 8+ years, of industry experience as mandate in Cell Biology, Molecular Biology, Developmental Biology, Immunology , or a related discipline.
Extensive experience designing and executing human disease models that directly inform therapeutic discovery and program decisions.
Demonstrated breadth across therapeutic modalities , including RNA-based therapies, enzyme therapeutics, and protein/antibody approaches, with an understanding of modality-specific constraints and opportunities.
Strong hands-on experimental background , including cell-based assays, functional biology, and imaging-based readouts, with the ability to rapidly prototype and de-risk new biology.
Experience selecting and applying sequencing, profiling, and molecular characterization technologies appropriate to biological questions, stage, and decision context.
Familiarity with automation, high-throughput experimentation, or AI/ML-enabled analysis , including the ability to partner effectively with computational teams to design scalable, data-rich experiments.
Proven ability to lead projects and mentor scientists in fast-moving, multidisciplinary environments without losing experimental rigor.
Track record of translating complex, high-dimensional biological data into clear, actionable scientific and therapeutic decisions.
Willingness and demonstrated ability to remain actively engaged at the bench while providing senior-level scientific leadership.

Nice To Haves

Exposure to multiplexed and high-dimensional functional assays , with experience building deep, disease-relevant readouts across multiple therapeutic areas.
Familiarity with functional genomics, single-cell, perturbation-based, and multi-omics approaches , including an understanding of experimental design tradeoffs and downstream analytical implications.
Experience with advanced imaging modalities , including spatial biology, 3D systems, or high-content phenotypic screening, and the ability to translate complex image-based data into biological insight.
Candidates are not expected to have hands-on mastery of every modality or technology, but must demonstrate strong scientific judgment in selecting and integrating the right approaches.

Responsibilities

Lead the design and execution of disease-relevant human model systems , selecting the appropriate level of biological complexity (engineered cell lines, primary cells, co-cultures, organoids, or advanced tissue systems) based on scientific questions and program stage.
Define disease-relevant phenotypes, perturbation strategies, and decision criteria that connect mechanism to therapeutic hypotheses.
Maintain hands-on experimental leadership (>30% bench time) to de-risk biology, prototype new models, and establish technical standards.
Design and implement quantitative, discovery-grade assays , including functional, imaging-based, and safety-aware readouts that are scalable and decision-enabling.
Enable and evaluate multiple therapeutic modalities (RNA, enzyme, antibody/protein-based approaches), assessing potency, kinetics, durability, delivery, and functional rescue in disease-relevant contexts.
Exercise scientific judgment in the selection and application of imaging, sequencing, and molecular profiling technologies , partnering with computational teams to ensure data is analysis-ready and impactful.
Integrate perturbation, multi-omics, and phenotypic data to uncover disease drivers, mechanisms of action, and translational biomarkers.
Serve as scientific lead across programs, mentoring scientists, guiding experimental strategy, and clearly communicating complex biological insights to internal and external stakeholders.
Rapidly assess new disease areas or modalities, defining minimum viable datasets to de-risk programs and accelerate decision-making.