"Senior Bioinformatics Analyst (AI/ML for Genomics) | Bioinformatics Resource Center"

Organization Overview

The Bioinformatics Resource Center (BRC) provides bioinformatics analysis, experimental design consultation, software infrastructure, and training to the scientific community at The Rockefeller University. With a specific expertise in the processing and analysis of high-throughput genomic sequencing data, and in collaboration with both wet and dry lab biologists, the BRC aims to support and accelerate the diverse and cutting-edge research conducted at the university through the creation of analytical pipelines; the analysis of biological data via direct collaborations; and the training of Rockefeller's faculty, students, and scientific staff.

Overview

The purpose of this position is to design, implement, and deploy applied AI/ML methods for genomics and multi-omics data within the Bioinformatics Resource Center (BRC). These efforts translate institutional AI strategy into robust, reproducible analytical pipelines that directly support research across Rockefeller University laboratories, implemented within existing BRC infrastructure and standards.

Responsibilities

Responsibilities include:

• Design, implement, and maintain AI/ML pipelines for genomics and multi-omics data (RNA-seq, ATAC-seq, ChIP-seq, functional genomics)
• Apply and adapt machine learning and deep learning models (e.g., convolutional and transformer-based architectures) to biological questions in collaboration with investigators.
• Develop interpretable models and attribution analyses (e.g., motif discovery, perturbation and variant-effect analyses) to support biological insight.
• Build, document, and containerize reproducible workflows suitable for shared HPC/GPU environments.
• Provide consultative support and training to researchers using BRC AI/ML tools and pipelines.
• Performs related duties & responsibilities as assigned/requested.

Qualifications

REQUIRED QUALIFICATIONS:

• Master’s degree in Bioinformatics, Computational Biology, Computer Science, or a related field
• A minimum of five years of relevant experience applying computational or machine learning methods to biological data.

PREFERRED QUALIFICATIONS:

• PhD in Bioinformatics, Computational Biology, Computer Science, or a related field
• Experience applying deep learning or foundation-model approaches to sequence-based or multimodal genomics data.
• Experience in a core facility or highly collaborative research environment.
• Familiarity with model interpretability for biological insight (motif analysis, attribution methods, TF/RBP modeling).
• Experience working with HPC/GPU resources and job schedulers (e.g., Slurm) and/or cloud-based deployments.
• Track record of contributing to peer-reviewed publications as a computational specialist.
• Interest in mentoring and training researchers in applied AI/ML methods.