Postdoctoral Associate - Computational biology and Bioinformatics
Indexed description
A Postdoctoral Associate is expected to collaborate closely with experimental biologists and clinicians. The position offers an extraordinary team-based science environment with opportunities for significant education, training, and career development.
This position offers a highly collaborative, team-based setting with opportunities for advanced training, mentorship, and career development.
Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.
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.
- Collaborates with experimental biologists and clinicians in the Cheng lab to apply computational and bioinformatics approaches to study cancer development, progression, metastasis, and prognosis.
- Designs, analyses, interprets complex datasets, and translates findings into biologically meaningful insights within a multidisciplinary research environment.
- Performs other job-related duties as assigned.
- MD or Ph.D. in Basic Science, Health Science, or a related field.
- No experience required.
- 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/PerlPython.
- Knowledge of basic molecular biology, genomics, and epigenetics.
- Experience in next-generation sequencing data and scRNA-seq data.
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