Senior Bioinformatics Programmer

The Petljak Lab is seeking a highly motivated and creative Senior Bioinformatics Programmer to join our multidisciplinary team within the newly established Cancer Genomics & Genetics Program at NYU Grossman School of Medicine. This is a highly collaborative, fast-paced, and scientifically engaged position suited to someone who thrives in an ambitious research environment, takes strong ownership of their work, and is motivated to drive projects forward. The position offers exposure to leading experts and collaborations across cancer biology, genomics, computational biology, and related disciplines.
The Petljak Labs research sits at the intersection of computational and experimental biology, cancer genomics, mutagenesis, and tumor evolution, with the goal of understanding how mutational processes arise and shape cancer development and therapeutic responseand using these insights to identify new opportunities for cancer prevention and treatment. Our work builds on recent studies deconvoluting mutational signatures from cancer genomes and using them as molecular readouts to identify the sources, mechanisms, and functional consequences of individual mutational processes (Cell, 2019; Nature, 2023; Nature Genetics, 2023; Cell Trends In Cancer, 2026).

The successful candidate will become a lead computational scientist within the lab, working closely with experimental scientists and clinical collaborators across multiple cancer genomics projects involving both patient specimens and experimental model systems. The core of the position is bioinformatics and computational analysis across the laboratorys research projects, primarily conducted within a high-performance computing (HPC) environment, with two main areas of focus: 1) analysis and interpretation of next-generation sequencing and large-scale genomic datasets, together with the development, execution, and maintenance of robust, reproducible analytical pipelines and workflows for these data types, including but not limited to whole-genome sequencing, whole-exome sequencing, RNA sequencing, and single-molecule/duplex DNA sequencing; and 2) development and implementation of creative computational approaches for specialized analyses across diverse datasets generated by cutting-edge experimental platforms and multimodal studies. Examples include custom genomic analyses, quantitative analysis of live-cell imaging data, and integration of genomic readouts with patient clinical features, environmental exposures, and other molecular and phenotypic data. Interest in thoughtfully evaluating and applying emerging AI-enabled tools to improve the efficiency, usability, and reproducibility of bioinformatics workflows and research operations is welcomed.

Supporting these core analytical responsibilities, the candidate will take ownership of developing and maintaining the laboratorys computational infrastructure, managing laboratory-generated and externally accessed datasets, and ensuring reproducibility and version control. The candidate will also coordinate with institutional HPC and IT teams, external vendors, and other service providers to troubleshoot and resolve needs related to computation and its supporting infrastructure as they arise.

The candidate will work with substantial independence while being deeply integrated into our research team based in the state-of-the-art CURE building at 345 Park Avenue South. Regular interactions with the Principal Investigator and lab members will provide opportunities to shape analytical strategy, contribute intellectually across multiple projects, mentor and supervise junior researchers and students, and help drive studies from experimental design through biological interpretation and publication.

Job

Responsibilities:

Bioinformatics Pipelines: Develop, execute, optimize, standardize, and maintain robust and reproducible bioinformatics pipelines for quality control and processing of next-generation sequencing datasets, establishing consistent analytical workflows and best practices across the laboratory's research projects.

Computational Analyses: Develop and implement custom computational approaches and software for downstream analysis, integration, visualization, and interpretation of sequencing and other specialized datasets generated across the labs research projects, including cutting-edge experimental platforms and multimodal studies.

HPC Computing & Troubleshooting: Ensure efficient and reliable execution of analytical workflows within the available HPC infrastructure, including troubleshooting and coordinating with the institutional HPC team as needed.

Reproducibility, Standardization & Version Control: Establish and maintain standardized computational workflows, analytical conventions, and best practices across the laboratory to ensure consistency and reproducibility of analyses. Maintain appropriate documen