Postdoctoral Research Scientist; Experimental

Position Summary

The Califano lab, in the Department of Systems Biology at Columbia University, is seeking exceptionally qualified candidates for a Postdoctoral Research Scientist position in the laboratory. Successful candidates will possess extensive expertise in wet-lab experimentation and advanced single-cell and spatial multi-omics technologies and will participate in highly competitive research programs aimed at producing innovative, high-impact publications.

The ideal candidate will have outstanding scientific credentials, including first-author publications in leading journals and presentations at major international conferences relevant to single-cell biology, spatial genomics, systems immunology, cancer biology, stem cell biology, or related fields. We are particularly interested in candidates with demonstrated expertise in the development and application of spatially resolved and single-cell technologies, including spatial transcriptomics, spatial ATAC-seq, multiplexed spatial proteomics, CITE-seq, Perturb-seq, CROP-seq, CRISPR-based perturbation systems, and advanced single-cell library preparation and profiling methods.

Candidates with strong backgrounds in immunology, cancer biology, stem cell biology, molecular and cellular biology, epigenetics, genetics, biomedical engineering, biochemistry, or related disciplines will be especially well suited. Experience integrating multimodal datasets—including transcriptomic, epigenomic and proteomic modalities—to define regulatory programs and cellular states within intact tissue architecture is highly desirable.

Integration of quantitative analysis, high-throughput experimentation, and technology development is a hallmark of our department and laboratory. Accordingly, the Postdoctoral Research Scientist will:

• Develop and apply cutting-edge spatial and single-cell multi-omics technologies to interrogate regulatory and signaling networks in complex tissue ecosystems.
• Define cell-state transitions and regulatory circuits in physiologic and pathophysiologic contexts with current focus on cancer.
• Design and implement CRISPR-based perturbation strategies (CRISPR, CRISPRi/a) to functionally test regulatory hypotheses derived from systems-level inference.
• Integrate genomic, epigenomic, and proteomic datasets to elucidate molecular determinants of cellular phenotypes and their spatial organization.
• Develop new methodological and computationally informed frameworks for dissecting regulatory logic and signaling network architecture within tissues.
• Collaborate across multidisciplinary teams spanning immunology, engineering, computational biology, pathology, and translational research.

While computational expertise is not strictly required, familiarity with large-scale genomic data processing, regulatory network inference, pathway analysis, immune and systems biology approaches will be considered a strong asset. The laboratory provides an intellectually rich environment in which experimental and computational scientists work closely together, and appropriate cross-training opportunities are available.

The successful candidate will be expected to thrive in a highly collegial and collaborative environment, mentor junior trainees, contribute to consortium-scale and multi-institutional projects, and participate in the preparation of fellowship and grant applications. Strong communication and scientific writing skills are essential.

Our laboratory has an outstanding record of training and career placement, with former members advancing to academic faculty positions (including leadership roles) and senior positions in biotechnology and pharmaceutical industries.

• PhD in molecular biology, immunology, cancer biology, genetics, epigenetics, stem cell biology, biomedical engineering, biochemistry, or a related field.
• Demonstrated record of first-author publications in peer-reviewed journals.
• Substantial experience with single-cell and/or spatial multi-omics methodologies.

• Expertise in spatial transcriptomics, spatial ATAC-seq, multiplexed proteomic imaging, and multimodal data integration.
• Experience with CRISPR-mediated gene…