The Departments of Radiation Oncology and Medicine at Columbia University Irving Medical Center in New York, NY has an opening for post-doctoral fellow for a combined position in the laboratories of two physician-scientists, Dr. Catherine Spina (Radiation Oncology) and Dr. Aleks Obradovic (Medicine) to start immediately. The position requires expertise in computational biology with an interest in immuno-oncology and translational oncology. Specifically, we are seeking candidates experienced working with transcriptional (scRNASeq, spatial Seq), genomic, and proteomic data who seek to build and integrate computational tools to develop novel approaches to analyze and integrate data derived from preclinical and clinical specimens. The successful candidate will interface with investigators in the laboratory who conduct mechanistic studies using experimental immunology techniques, pre-clinical tumor models, and leverage human tissue (tumor) specimens for single-cell analytic approaches, including flow cytometry, quantitative multiplex immunofluorescence, scRNASeq and spatial Seq (Visuium).
Our laboratories stand at the interface of academic translational immune-oncology including collaborations with leading academic oncologists, translational and basic scientists, industry partners, and early phase clinical trials. The role offers the opportunity to gain experience in both the academic and industry environments to prepare the successful candidate for a role either. We are seeking candidate who aims to drive mechanistic study in a multidisciplinary fashion through intersection of oncology, tumor immunology, genomics, radiation biology, systems biology. The successful candidate will have the opportunity to be involved in investigator-initiated and early phase clinical trials for clinical translation.
The Spina laboratory is focused on understanding the immunologic implications of tumor irradiation, including innate and adaptive resistance mechanism, and elucidation of mechanisms driving these changes. Our aim is to translate our mechanic insight into novel therapies for combination with radiation to improve patient outcomes. The results of this research will be communicated by published outcomes in high-impact journals by our group, new investigator-initiated clinical trials, and offer collaborative opportunities with academic and industry partners.
The Obradovic laboratory is focused on developing computational tools for analysis of single-cell RNA sequencing and multimodal data types and applying these tools for improved understanding of tumor immunotherapy resistance mechanisms and prioritization of rational combination therapies. This work builds on multi-omic studies across clinical trials in kidney, prostate, head and neck, as well as other tumor types. Ongoing work is highly collaborative with senior faculty in the Department of Systems Biology led by Andrea Califano as well as the Center for Translational Immunology.
We are seeking candidates with at least 5 years? experience in computational biology. Self-motivated and creative individuals with a track record in the field of immunology/tumor immunology and/or oncology, with relevant publications and an interest in translational opportunities should apply. Successful candidates should have excellent written and oral communication skills, and comfort training junior members of a laboratory.
Qualified candidates should hold a Ph.D. degree in medical sciences or a related discipline with a proven record of peer-reviewed publications.
Please provide a cover letter explaining relevant work experience and interests, your CV, and the contact information for three references.
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.
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