Decode the regulatory genome

We are entering a new era in genomics with exciting opportunities for computation-driven discovery. Our aim is to explore the new possibilities of what computation can do for biomedical science, from understanding sequence-based regulation to the evolution of genomes and their impact on disease.

Lab news, September 2025: Zhou Lab is now based in the Section of Genetic Medicine, Department of Medicine, University of Chicago.

We develop machine learning and AI methods to understand biology.

Genome sequence encodes the regulatory programs that control cellular function. We develop machine learning methods to connect sequence with chromatin organization, 3D genome architecture, gene expression, and disease phenotypes. Our goal is to predict, interpret, and design genomic sequences.

Evolution of Regulatory Genome

Prior work: Science 2024 (Puffin), Nature Genetics 2018

Sequence, function, and evolution are tightly linked across genomes. We develop computational methods to reconstruct how regulatory circuits arise and change across species, using data from both model and non-model organisms. We are especially interested in how evolutionary changes in regulation shape human traits and disease.

We develop AI systems that can accelerate discovery in computational biology. Our long-term goal is to build methods that assist, scale, and increasingly automate biological research.

Join us

Open Positions:

We are looking for curious, rigorous, and creative researchers who want to develop new machine learning methods and apply them to fundamental problems in genomics. Please contact me at jianzhou@uchicago.edu if you are interested in joining the lab.

Graduate Student

If you are interested in joining our lab as a graduate student, please apply through one of the relevant graduate programs at the University of Chicago, such as the GGSB gradaute program. We will help students develop a strong analytical mindset and knowledge for conducting cutting-edge research with computational approaches.

Postdoctoral Fellow

We are looking for postdoctoral fellows to work at the intersection of genomics and AI. Ideal candidates should have Ph.D. or equivalent degrees in Computational Biology, Computer Science, Statistics, or a related field at the expected start time. Prior research experience in any areas including regulatory genomics, statistical or evolutionary genetics, single-cell genomics, computational structural biology, machine learning, or statistics is a plus but not required. This is a full research position, but teaching opportunities can be provided if desired. If interested, please email your CV, a brief description of your previous works, and your future research interests to jianzhou@uchicago.edu.

Undergraduate Student

We welcome motivated undergraduates to join our team. We are happy to train undergraduates in many aspects of computational biology and data science. Please contact Jian to discuss research opportunities.

The Zhou Lab is located in the University of Chicago campus in Hyde Park. Lab members also have access to considerable computational resources, including state-of-the-art GPU computing server clusters to support our deep learning research.