The Department of Psychiatry at Columbia University Irvine Medical Center seeks a highly qualified and a motivated postdoctoral research associate to conduct method development and data analysis focused on genomics of complex human traits and brain-related disorders. The role involves applying statistical, computational, and machine learning methods to large-scale genomic and phenotypic datasets from clinical cohorts and population biobanks. The successful candidate will analyze whole-genome sequencing data and gene expression data alongside rich multimodal phenotypes to study the effects of common, rare, and structural genetic variation. The work aims to identify genetic risk factors, relevant genes, and biological pathways underlying psychiatric conditions. The position is embedded in an interdisciplinary, collaborative research environment and is suitable for candidates pursuing academic or industry research careers. Visa sponsorship may be available.

Job Function :

Develop and apply scalable statistical, computational, and machine learning methods for large-scale genomic and phenotypic data. Build, document, and maintain robust, reproducible analysis pipelines. Participate and eventually lead research projects from conception to publication. Collaborat with computational and clinical researchers to interpret results. Prepare manuscripts for peer review publication and present findings at scientific meetings. Mentor junio researchers and contribute to group activities. Advance by obtaining grant support for transaction to faculty appointment.

Lab Mission/Purpose:

The research team, led by J. John Mann, MD, Paul Janssen Professor of Translational Neuroscience (in Psychiatry and in Radiology), investigates the neurobiological foundations of mood disorders and suicidal behavior. Integrating functional brain imaging, neurochemistry, molecular genetics, and neuropathology, the team seeks to identify biomarkers and causal mechanisms underlying depression and suicide risk. By linking clinical presentation with measurable brain and molecular alterations, the group aims to refine risk prediction, improve treatment selection, and advance prevention strategies. The work emphasizes translational impact, bridging basic neuroscience and clinical psychiatry to inform evidence-based care and reduce the burden of depressive illness. In parallel, collaboration with Tarjinder (TJ) Singh, PhD,advances a genomics-driven investigation of severe psychiatric disorders, including schizophrenia, major depression, and bipolar disorder. Leveraging large-scale international sequencing consortia and population biobanks, the team identifies risk genes, characterizes the clinical impact of common and rare variants, and integrates genetic with functional data to define implicated cell types, circuits, and biological pathways. This work aims to clarify disease mechanisms and generate biologically grounded hypotheses that enable the development of novel, mechanism-based therapies. PhD in Genetics, Statistics, Biostatistics, Computational Biology, Bioinformatics, Computer Science, Epidemiology, or a related field. Proficiency in at least one modern programming language (e.g., Python, Java, C/C++) and in R for statistical analysis. Experience with Unix/Linux environments and high-throughput genetic data analysis. Familiarity with genomics or other -omics pipelines (e.g., WGS, RNA-seq) and relevant tools. Experience with reproducibla research and software engineering best practices (e.g., version control, containerization). Ability to work independently and collaboratively, with strong communication skills.

Preferred Qualifications :

Strong technical rigor and ability to manage complex projects. Effective collaboration and clear scientific communication Adaptability, initiative, and interest in methodological innovation. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University?s good faith and reasonable estimate of the range of possible compensation at the time of posting.