About the Lab
The Zhou Lab at UMass Chan Medical School (UMass Chan) develops and applies cutting‑edge computational and big‑data approaches to understand the genomics, epigenomics, and regulatory functions of noncoding RNAs in human disease. We develop computational methods and scalable pipelines to decode noncoding RNAs and their epigenetic modifications from diverse high-throughput sequencing data—advancing precision diagnostics and therapeutics.
Lab Research
* AI-Driven Algorithms & Software: Develop algorithms and user-friendly software to profile RNA modifications, circular RNAs, lncRNAs, and fusion transcripts—and to predict RNA-based biomarkers and therapeutic targets.
* Integrative Analysis of Multi-Omics data: Build end-to-end workflows for bulk and single-cell RNA-seq, long-read sequencing, and epigenomic assays, enabling efficient processing of large-scale, multi-omics datasets and apply them to decipher human diseases.
* Translational Discovery Integrate computational findings with clinical and genetic data using machine learning/deep learning methods to identify RNA signatures of disease, guiding the development of RNA-based diagnostics and precision-medicine strategies.
Research Environment
* World‑Class Environment: Located in the Albert Sherman Center alongside Nobel laureates Victor Ambros and Craig Mello.
* Top‑Tier Collaborations: Close ties with leading scientists and clinicians at Harvard Medical School, MIT, and UMass Memorial Health.
* Prime Location: Worcester, MA—an affordable satellite city 50 minutes from Boston by train, with a vibrant academic community and lower cost of living.
* Career Development: Dr. Zhou provides tailored mentorship and resources to align your postdoctoral training with your career goals, whether academic, industry, or beyond.
* Ph.D. (or imminent defense) in Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Statistics, Biophysics, Biomedical Engineering, or a related field.
* Strong programming skills in at least one of: Python, R, C/C++, or Perl; proficient with Unix/Linux.
* Experience with deep learning, statistical modeling, or AI applications to biological data.
* Familiarity with transcriptomic technologies, ideally single‑cell RNA‑seq or long‑read sequencing.
* Demonstrated ability to conduct independent research and publish as first/co‑author.
* Excellent communication, teamwork, and project‑management skills.
Please email the following to Dr. Chan Zhou at chan.zhou@umassmed.edu (subject line: “Postdoc Application – Your Name”):
* Cover Letter: Summarize your research background, interests, and career objectives.
* Curriculum Vitae: Include publication list and detailed computational skill set.
* References: Contact information for at least two referees (email and phone).
UMass Chan Medical School is committed to fostering a diverse and inclusive environment. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.