The Precision Genetics group in the Data, AI and Genome Sciences Department seeks a Postdoctoral Research Fellow to drive computational work on a translational project developing a reusable multi-omics and AI/ML framework to discover mechanism-based companion diagnostic (CDx) biomarkers that predict treatment response in autoimmune diseases

• The role combines organoid drug-profiling, multi-modal functional assays, single-cell and spatial transcriptomics, and development of interpretable AI/ML models to identify predictive biomarkers and benchmark model fidelity against clinical datasets
• Analyze multi-modal pre- and post-treatment readouts, including epithelial barrier assays, cytokine profiling, single-cell RNA-seq, and spatial transcriptomics (e.g., 10x Visium, GeoMx, Stereo-seq)
• Develop, benchmark, and maintain reproducible computational pipelines for bulk, single-cell, and spatial transcriptomics data processing (QC, alignment, cell-type annotation, and spatial analyses)
• Implement multi-omic integration strategies combining spatial transcriptomics, single-cell expression, cell composition estimates, and genotype/SNP data
• Design, train, evaluate, and interpret AI/ML models (supervised and unsupervised) for predictive biomarker discovery and companion diagnostic candidate prioritization, emphasizing feature selection and model explainability
• Document methods, workflows, and results thoroughly; prepare and contribute to manuscripts, conference presentations, and IP/translation activities as appropriate
• Collaborate effectively with wet-lab scientists, clinicians, and computational colleagues, present results to the team and stakeholders

This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely

• Demonstrated experience analyzing single-cell and/or spatial transcriptomics data processing, clustering, differential expression, spatial analysis)
• Proven ability to apply advanced AI/ML to biomedical data for biomarker discovery/patient stratification, using rigorous evaluation and reproducible Python/R pipelines
• Strong statistical skills and experience working with high-dimensional biological data; excellent data visualization abilities
• Excellent written and oral communication skills and evidence of productivity appropriate to career stage (publications, code repositories, or preprints)

Proven ability to work collaboratively in interdisciplinary teams and manage multiple projects concurrently postdoctoralopportunities

• Ph.D. or completion within 6 months in Computational Biology, Bioinformatics, Systems Biology, Genomics, Biomedical Engineering, Computer Science (with bioinformatics experience), or related discipline
• Strong programming skills in Python and/or R and familiarity with relevant libraries/tools (Seurat, Scanpy, Squidpy, Bioconductor, scikit-learn, PyTorch/TensorFlow)

Bioinformatics, Computational Analysis, Datasets, Large Scale Data Processing, Scientific Writing, Single-Cell Genomics, Wet Lab