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

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

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. The Rockefeller University is an equal opportunity employer – veterans/individuals with disabilities.

Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status. The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training.

The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Compensation

Min USD $90,000.00/Yr.

Compensation

Max USD $115,000.00/Yr.

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.

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. The Rockefeller University is an equal opportunity employer – veterans/individuals with disabilities.

Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status. The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training.

The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.