Instructor in Medical Sciences at the CUMC

Instructor in Medical Sciences (in Medicine) at the CUMC

The Kiryluk lab in the Division of Nephrology at Columbia University Irving Medical Center is seeking an Instructor in Medicine to engage in genetic, genomic, and experimental research on urinary tract infections. Applicants should have demonstrated experience with animal studies of urinary tract infections, they should also be able to execute large-scale bioinformatic analyses of human genetic and phenotypic data, including electronic health record (EHR) data, whole genome sequence (WGS) data, whole exome sequence (WES) data, genome-wide association study (GWAS) data, as well as single cell and bulk RNA-seq data of patients with urinary tract infections.

The position requires relevant experience in biostatistics, bioinformatics, computational biology, genetics or similar field of study. Experience needed in GWAS and NGS data analysis, proficiency with PLINK and R statistical analysis, exposure to Next Generation Sequencing (NGS), familiarity with the tools for genome and transcriptome interpretation, familiarity with the statistical principles and methods relevant to computational genomics.

Must be collaborative and able to work in a fast-paced environment with an ability to multitask. Individual must be team oriented, possess excellent written and verbal communication skills, as well as be able to demonstrate strong creative thinking and problem-solving skills.

Candidates must have PhD or MD/PhD degree, excellent communication skills, advanced organizational skills, a strong work ethic, and the ability to work independently.

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.