Bioinformatician (Staff Associate II)

Overview This opportunity to join the Department of Pediatrics at the Vagelos College of Physicians and Surgeons at the rank of Staff Associate II is an exciting one. Columbia University Irving Medical Center is one of the nation’s foremost academic health science centers. The Department of Pediatrics at Columbia University Irving Medical Center is amongst the leading pediatric departments in the New York region and NIH research funding. Responsibilities Children’s Health Redox Center (CHRC), NY, USA is seeking a hard-working and enthusiastic Bioinformatician to join a multidisciplinary program focused on multi-omics, particularly lipidomics and redox lipidomics, and mass spectrometry-based spatial biology. The candidate will contribute to the development and application of multiplex omics approaches and advanced data analysis tools that enable mechanistic understanding of the pathophysiology of neurological disease and critical illness, and the discovery of new diagnostic tools and therapies. The role requires collaboration with researchers with backgrounds in bioinformatics, image analysis and spatial multimodal data integration, computational vision, systems biology or computational biology, and a commitment to team-based science. Qualifications Master’s degree in bioinformatics, computer science, or systems biology. 2-3 years of experience; PhD degree in related field would substitute for experience. Consistently strong interpersonal skills and the ability to build and sustain effective working relationships with professionals in other disciplines. The ability to create a high-energy results-oriented work environment that encourages colleagues and staff to value each other’s contributions; and must be able to work in a team-oriented environment and demonstrate attention to detail and record-keeping. The ability to share and celebrate success with colleagues and staff. Ability to apply and be proficient in R, C++, Perl/Python, and shell scripting in Linux environment. Experience with machine learning, LLMs and AI approaches. Training in biostatistics, image analysis, machine learning, and/or database management are desirable assets. Prior experience in analyzing single-cell and bulk RNAseq, ATACseq and/or ChlPseq data (and other NGS datasets) is also desirable. Prior experience with computational models for image analysis and multimodal integration is desirable. #J-18808-Ljbffr Columbia University