AI-Enabled iPSC Disease Modeling & Functional Genomics in Cambridge

AI-Enabled iPSC Disease Modeling & Functional Genomics

Location:

Cambridge, MA

Sanofi is building a next-generation neuroscience research engine focused on defining the molecular mechanisms of neurodegenerative disease - Alzheimer's disease, ALS, frontotemporal dementia, Parkinson's disease, and multiple sclerosis - through high-resolution interrogation of human models and tissue. We are seeking a Senior Research Associate II to develop and deploy human iPSC-derived cellular models and CRISPR-based functional genomics to interrogate TDP-43 biology and other priority pathways, and to deliver fit-for-purpose assays that drive internal discovery programs.

This role sits at the experimental engine of the group. The successful candidate will design, generate, and characterize isogenic iPSC lines and iPSC-derived glial and neuronal cultures; build robust phenotypic assays suitable for hit-finding and target validation; and contribute to pooled and arrayed CRISPR screens that uncover genetic modifiers of disease-relevant phenotypes. The role partners closely with computational biologists, neuropathologists, and program teams to translate human cellular insights into actionable drug discovery hypotheses.

Join the engine of Sanofi's mission - where deep immunoscience meets bold, AI-powered research. In R&D, you'll drive breakthroughs that could turn the impossible into possible for millions.

Main responsibilities:

• Maintain, expand, and quality-control human iPSC lines; generate and validate isogenic disease-relevant lines using CRISPR/Cas9, base editing, and prime editing (knock-in, knock-out, and tagged reporter alleles).
• Differentiate iPSCs into disease-relevant CNS cell types - including microglia, astrocytes, oligodendrocyte-lineage cells, and motor and cortical neurons - using established and emerging protocols; develop and optimize co-culture and tri-culture systems as needed.
• Build and validate fit-for-purpose cellular assays to interrogate TDP-43 biology and other priority mechanisms, including cryptic exon readouts (e.g., STMN2, UNC
  13A, HDGFL2), TDP-43 mislocalization and aggregation, cellular stress responses, and disease-relevant functional endpoints.
• Develop high-content imaging and plate-based assays (96- and 384-well formats) suitable for compound screening, target validation, and mechanism-of-action studies; partner with screening and ADME groups to qualify assays for internal use.
• Apply AI/machine learning-based image analysis approaches for cellular phenotyping and high-content readouts, in partnership with computational team members.
• Contribute to the design, execution, and analysis of pooled and arrayed CRISPR screens (CRISPRko, CRISPRi, CRISPRa) in iPSC-derived models, including library handling, lentiviral packaging, transduction, FACS- or imaging-based selection, and single nuclei RNA and ATAC seq sample preparation.
• Generate and maintain stable cell lines, lentiviral reporter systems, and inducible expression systems to support discovery programs.
• Maintain rigorous electronic lab notebook records, contribute to internal data reviews, present results at group and cross-functional meetings, and contribute to publications, posters, and patent filings.
• Develop, optimize, and document standard operating procedures; train junior team members on established assays and platforms.
• Coordinate with external academic collaborators and CRO partners on cell line generation, screen execution, and assay transfer.

About You

Education:

• BS with 4+ years OR MS with 2+ years, of relevant laboratory experience in stem cell biology, neuroscience, molecular biology, cell biology, or a related discipline.

Experience & Technical

Skills:

• Demonstrated hands-on proficiency in human iPSC culture, banking, karyotype/STR/pluripotency QC, and directed differentiation into at least one CNS cell type (microglia, astrocytes, oligodendrocyte-lineage cells, or neurons).
• Hands-on experience developing plate-based and/or high-content imaging assays, including assay miniaturization, Z'-factor and reproducibility assessment, and basic statistical interpretation of phenotypic data.
• Familiarity with high-content imaging platforms (e.g.,…