Postdoctoral Associate | Vertebrate Genome Laboratory

The Rockefeller University; New York (NY); On-site; USD 70,000 - 95,000; Full time

Job summary

The Rockefeller University invites applications for a Postdoctoral Associate in the Vertebrate Genome Laboratory to advance conservation genomics and population genetics within GAIA—Genomic Artificial Intelligence Applications. The role combines genomic data analysis with AI-driven genome curation and conservation decision support for non-human species.

You will lead population- and evolutionary-genomics analyses, identify meaningful conservation questions, and collaborate with AI scientists to

Qualifications

• Expertise in conservation genomics and population genetics.
• Experience in computational biology approaches.
• Ability to collaborate with AI scientists and engineers.

Responsibilities

• Lead computational analyses in population, evolutionary, and conservation genomics across non-human species.
• Identify conservation use cases to guide GAIA tool development and evaluation.
• Review historical genomic applications in conservation linking data to outcomes.

Skills

Conservation genomics

Population genetics

Computational biology

Job description

Organization Overview

The Vertebrate Genome Laboratory (VGL) atThe Rockefeller Universityleads international efforts in vertebrate genome sequencing, assembly, annotation, and evolutionary analysis. As a core laboratory of theVertebrate Genomes Projectand a major hub of theEarth BioGenome Project, VGL is at the forefront of generating high-quality, telomere-to-telomere genome assemblies across vertebrate diversity.The laboratory provides an end-to-end genomics platform spanning sample processing, sequencing, genome assembly, and downstream data analytics. It specializes in high-molecular weight DNA extraction and long-read genomic technologies, offering integrated library preparation and sequencing services for high–molecular weight genomic DNA, long amplicons, and full-length transcriptome sequencing (Iso-Seq). These capabilities are tightly coupled with in-house computational expertise for genome assembly, curation, annotation, and comparative genomics, and are supported by state-of-the‑art platforms including PacBio and ONT.

Overview

We seek a Postdoctoral Associate with expertise in conservation genomics, population genetics, and computational biology to join GAIA—Genomic Artificial Intelligence Applications—a collaborative initiative among The Rockefeller University, Revive & Restore, Cornell University, and other academic and technology partners, supported by the Bezos Earth Fund and Google.org.

GAIA is developing next-generation artificial-intelligence systems that scale genome assembly and enable rapid genome-informed conservation decision making. Its two central goals are:

• To build Jarvis, an AI Genome Curation Assistant that combines machine-learning approaches with large-scale biological data to detect, interpret, and correct structural errors in genome assemblies, substantially reducing the manual effort required to produce high-quality reference genomes.
• To build Genera, a multimodal, agentic AI system that integrates genomic, ecological, and other biological data to assess extinction risk and generate actionable genetic-rescue strategies for conservation practitioners.

The successful candidate is interested in applying genomic research to biodiversity conservation and species recovery and will provide the population-genetic, evolutionary, and conservation-genomics expertise needed to guide the technical development, validation, and application of these systems. The Postdoctoral Associate will work closely with AI scientists and engineers across partner institutes, providing complementary skills and knowledge in biodiversity genomics.

The position will focus solely on non-human species and will connect high-quality reference genomes and population-level genomic data to real-world questions in
biodiversity conservation. The candidate will also help establish an evidence base connecting prior uses of genomic information, conservation decisions, and documented recovery outcomes. Potential research areas include genetic diversity and inbreeding, demographic history, deleterious variation and genetic load, local adaptation, reproductive failure, disease susceptibility, population viability, and predicting the genomic consequences of potential conservation interventions.

The candidate will have substantial opportunity to shape an independent research program within this broad framework and to develop applications across diverse endangered and recovering species.

Responsibilities

Responsibilities include, but are not limited to:

• Lead computational analyses in population, evolutionary, and conservation genomics across non-human species.
• Identify biologically meaningful questions, genomic features, and conservation use cases that can guide the development and evaluation of GAIA tools.
• Review and synthesize historical applications of genomic data in conservation, linking the genomic evidence used, the management interventions undertaken, and the resulting conservation outcomes