Postdoctoral Associate - Computational Biology And Bioinformatics The Cheng Lab in the Department of Medicine, Section of Epidemiology & Population Sciences is searching for highly motivated and talented post-doc candidates to work on Bioinformatics and Computational Biology in Cancer Genomics and Immunology. This position will be involved in the development and/or application of computational approaches to understand the mechanism of cancer development, progression, metastasis, and prognosis. The Postdoctoral Associate should have experience in processing and analyzing data from the next-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable. The position offers an extraordinary team-based science environment with opportunities for significant education, training, and career development. Baylor College of Medicine is located at the Texas Medical Center, which is the largest medical complex in the world and provides an ideal environment for scientific and clinical research.
Job Duties:
Develops and/or applies computational approaches to understand the mechanism of cancer development, progression, metastasis, and prognosis.
Collaborates closely with experimental biologists and clinicians to design studies, validate computational findings, and support translational applications of research discoveries.
Participates in regular joint meetings to present findings, discuss ongoing projects, and align research strategies with lab and departmental priorities.
Assists in mentoring and training of junior researchers in computational techniques and bioinformatics best practices.
Translates complex computational results into biologically meaningful insights in collaboration with wet-lab teams.
Maintains thorough documentation of analyses, pipelines, and datasets in version-controlled environments.
Minimum Qualifications:
MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required.
Preferred Qualifications:
PhD in Computational Biology, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology).Experience in the application and development of computational methods/tools or machine learning algorithms.
Good computer programming skills in R/Matlab/Perl/Python.
Knowledge of basic molecular biology, genomics, and epigenetics.
Experience in next-generation sequencing data and scRNA-seq data.
