General Summary of the Position
Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865). 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, including bulk, single-cell, and long-read sequencing data.
Lab Research:
• AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in human genetics and disease, toward developing RNA-based therapeutics.
• 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.
The successful candidate will benefit from collaboration with world-class scientists and physicians at UMass Medical Center and in the Greater Boston area, including Harvard/MIT and other prestigious institutes. Dr. Zhou provides tailored mentorship and resources to align postdoctoral training with career goals, whether in academia, industry, or beyond.
REQUIRED QUALIFICATIONS:
Application Instructions
Please email the following to Dr. Chan Zhou at chan.zhou@umassmed.edu (subject line: “Postdoc Application – Your Name”):
Equal Opportunity Employer
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.
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