Precision cancer medicine is a rapidly developing field that started with the introduction of genomic profiling to guide cancer therapy. However, there are great potentials to expand the field of precision cancer medicine to integrate emerging genomic and computational approaches with deeper experimental approaches to define new ways to exploit cancer biology to develop new therapies and new ways to prevent and detect cancer. The new Center for Precision Cancer Medicine at Columbia University aims to tackle these challenges.
Our center is looking for a highly motivated Associate Research Scientist to lead a new team working on development of new approaches to integrate functional genomics with more complex cancer models (in vitro and in vivo) and detailed genomic readouts of experiments (i.e. single cell technologies and spatial transcriptomics). Key goals will be to define biomarkers to guide cancer therapy, build towards development of rational combination therapies and to identify novel cancer targets. This position will have a large component of bench research but will require interaction with a multi-disciplinary team spanning other faculty/research scientists working in the spheres of functional genomics, fundamental cancer biology, computational biology and development of novel cancer models. We anticipate in the near future expansion to addressing the intersection of functional genomics with immunotherapy and chemical biology. A successful candidate will work collaboratively to develop and refine new approaches, work with diverse investigators to disseminate tools and expertise and play key roles in large collaborative projects.
Ph.D. (or MD with post-doctoral experience) with a preference for additional training following doctoral studies.
Strong publication, in-depth knowledge and hands-on experiences using a wide range of cellular and molecular biology techniques. We will show preference for candidates with experience in functional genomic screening (CRISPR and/or shRNA based approaches used for standard screens in 2D cell culture and with screening in more complex model systems.
Knowledge and experience running conventional functional genomics data analysis pipeline (e.g. MAGeCK, BAGEL) are preferred.
Experiences in running functional enetic screens with validation of targets for follow-up is highly desired.
Experiences with genomic and epigenetic profiling techniques (CHiP-seq, ATAC-seq), single-cell RNA-seq and/or deconvolution of pooled genomic screens would be a plus.
Demonstrated independence in experimental design, execution, data analysis, and troubleshooting.
Attention to detail with excellent organizational and record keeping skills.
Preferred experience managing multiple concurrent projects across multidisciplinary teams and supervising laboratory personnel.
Excellent communication skills and interpersonal skills
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.
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.