Senior Bioinformatics Programmer

NYU Langone Health•New York, NY

6d•$90,000 - $115,000•Onsite

About The Position

The Petljak Lab at NYU Grossman School of Medicine is seeking a highly motivated and creative Senior Bioinformatics Programmer to join their multidisciplinary team within the Cancer Genomics & Genetics Program. This role is ideal for someone who thrives in a collaborative, fast-paced research environment and is driven to advance projects. The position offers exposure to leading experts and collaborations across cancer biology, genomics, and computational biology. The lab's research focuses on understanding how mutational processes in cancer develop, shape cancer, and influence therapeutic response, aiming to identify new prevention and treatment strategies. The successful candidate will be a lead computational scientist, working closely with experimental scientists and clinical collaborators on cancer genomics projects. The core responsibilities involve bioinformatics and computational analysis of next-generation sequencing and large-scale genomic datasets, including developing, executing, and maintaining robust analytical pipelines. This includes whole-genome sequencing, whole-exome sequencing, RNA sequencing, and single-molecule/duplex DNA sequencing. Additionally, the role involves developing and implementing creative computational approaches for specialized analyses of diverse datasets from cutting-edge experimental platforms and multimodal studies, such as custom genomic analyses, quantitative analysis of live-cell imaging data, and integration of genomic data with clinical features and other molecular/phenotypic data. The position also welcomes interest in evaluating and applying AI-enabled tools to enhance bioinformatics workflows. Supporting these analytical tasks, the candidate will manage the laboratory's computational infrastructure, handle data management, and ensure reproducibility and version control. Collaboration with institutional HPC and IT teams, external vendors, and service providers is also expected for troubleshooting computational needs. The candidate will work with significant independence, be integrated into the research team, and have opportunities to shape analytical strategy, contribute intellectually, mentor junior researchers, and drive studies from design to publication.

Requirements

Ph.D. or M.Sc. in Bioinformatics, Systems Biology, Computer Science or related field.
Knowledge of cancer biology and understanding of key concepts in cancer genomics.
3+ years of experience with next-generation DNA sequencing data, with significant experience in building computational pipelines for analyses of sequencing data.
Experience in effectively managing multiple concurrent projects.
Demonstrated advanced proficiency in Unix/Linux systems including HPC environments and containerization.
Demonstrated advanced proficiency in developing customized, reproducible bioinformatics pipelines using Snakemake, Nextflow, or similar workflow management system.
Demonstrated advanced proficiency in using version control systems such as Git/GitHub.
Strong understanding of statistical principles and demonstrated ability to select and apply appropriate statistical methods for the analysis and interpretation of genomic and other biological datasets.
Scripting languages: R and Python.
Ability to work independently while collaborating effectively with team members and contributing to shared research goals.
Excellent communication skills and proficiency in written and oral English.

Nice To Haves

Ph.D. preferred

Responsibilities

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.
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.
Ensure efficient and reliable execution of analytical workflows within the available HPC infrastructure, including troubleshooting and coordinating with the institutional HPC team as needed.
Establish and maintain standardized computational workflows, analytical conventions, and best practices across the laboratory to ensure consistency and reproducibility of analyses. Maintain appropriate documentation and version control using Git/GitHub and workflow management systems such as Snakemake or Nextflow.
Develop and maintain effective systems for the storage, organization, curation, processing, access, and sharing of the laboratory's genomic and other research data, as well as large-scale external datasets used by the lab. This includes managing appropriate computational resources and technologies such as internal servers and SLURM-based compute clusters, MariaDB, Docker/Singularity, Git/GitHub, Google Cloud, and Google Drive, and coordinating access, approvals, and ongoing management of controlled-access datasets as required.
Oversee the laboratory's day-to-day computational and software needs, proactively addressing issues and coordinating with institutional HPC and IT teams, software vendors, and other service providers as needed.
Interpret data in close collaboration with experimental scientists and clinical collaborators; present and summarize findings to the research team and clearly communicate analytical approaches, results, limitations, and biological implications. Support the team in its research goals.
Remain current with advances in cancer genomics, bioinformatics, and computational biology, and independently identify, learn, and implement new computational methods, software, and programming approaches required by evolving research needs.
Perform other responsibilities related to the laboratory's evolving computational, bioinformatic, and analytical needs as required.