Scientist, Complex in Vitro Systems (Lung Focus)

Position Title: Scientist, Complex in Vitro Systems (Lung Focus)

Work Location: South San Francisco, CA, 94080

Assignment Duration: 12 Months

Work Arrangement: Onsite (M-F, 8 h a day)

Position Summary:

The Complex in Vitro Systems (CiS) Lab within the Department of Translational Safety is seeking a highly motivated Scientist to develop, characterize, and qualify advanced complex in vitro models to support The Organization's mission of delivering safe and efficacious medicines. The CiS group partners closely with colleagues across Development Sciences, Translational Medicine, and Research to establish and implement innovative platforms that enable target assessment, lead optimization, and safety evaluation across a dynamic portfolio, novel modalities, and emerging therapeutic areas.

Background & Context:

In this lab-based role, you will provide scientific and technical expertise to support the development and implementation of human lung complex in vitro models (CIVM), including lung organoids, air-liquid interface (ALI) cultures, and lung microphysiological systems for drug development.

Key Responsibilities:

* Development, qualification, and implementation of innovative in vitro lung model systems (e.g., airway and alveolar organoids, ALI cultures, lung-on-a-chip co-culture platforms) to support disease modeling and lung safety risk assessment.

* Designing and executing experiments to characterize lung models, including evaluation of cell viability, morphology, and barrier integrity and function, using techniques such as cytotoxicity assays, confocal and high-content imaging, transepithelial resistance/permeability assays, and transcriptomic and proteomic analyses.

* Collaborating closely with cross-functional teams within and outside gRED to align on complex model building with therapeutic strategies and program needs.

* Analyzing, interpreting, and clearly communicating study results to collaborators and stakeholders, and contributing to internal and external scientific presentations as appropriate.

* Maintaining comprehensive electronic documentation in accordance with departmental Standard Operating Procedures (SOPs) and contributing to study reports, safety assessments, and final deliverables.

* Culturing and characterizing state-of-the-art lung CIVM models, designing and executing model qualification and characterization studies (e.g., advanced imaging, transcriptomics, and functional and phenotypic assays), analyzing and interpreting complex datasets.

* Sharing scientific insights across functional teams, contribute to cross-disciplinary collaborations, and support internal and external publication efforts.

Qualification & Experience:

* PhD in Bioengineering, Cell Biology, Molecular Biology, Toxicology (or related fields) with 0-5 years of experience post-PhD with hypothesis-driven research in industry or academia.

* Experience in culturing multiple lung cell types, including relevant lung primary cells and cell lines.

* Proven expertise in developing, qualifying, and applying airway or alveolar organoids, co-culture systems, and microphysiological or microfluidic platforms, to support drug discovery and translational research.

* Proficiency with quantitative and qualitative characterization techniques such as qRT-PCR, RNA-seq, proteomics, immunofluorescence and confocal microscopy, live-cell and time-lapse imaging, high-content imaging/screening, and analysis of data generated from these assays.

* Strong experimental design skills, with demonstrated ability in troubleshooting, method development, and protocol optimization for complex in vitro systems.

* A collaborative, team-oriented scientist who prioritizes shared objectives and communicates effectively across disciplines, with a strong work ethic grounded in scientific rigor, attention to detail, and a commitment to excellence.

Preferred Qualifications:

* Experience lung biology and immunology is a strong plus.

* Advanced proficiency in MATLAB and/or Python for image processing, algorithm development, and large-scale data analysis.