Summary

The Stem Cell and Regenerative Medicine (STaR) Center at Baylor College of Medicine (https://www.bcm.edu/research/research-centers/star-center) focuses on mechanisms regulating stem cell self-renewal and differentiation across developmental stages and tissue types. Baylor College of Medicine is widely recognized for its exceptional, innovative, and collaborative research environment. It is investing significant resources in expanding interdisciplinary research in the computational, genomic, cellular, and molecular bases of human health and disease. The labs in the STaR center apply state-of-the-art computational strategies to contribute significantly to biomedical research while fostering career development. The STaR center is in the Texas Medical Center, the largest biomedical complex in the world, immediately adjacent to Houston’s vibrant Museum District and Hermann Park. A Sr. Bioinformatics Analyst position is available immediately in the STaR center. The individual will identify and implement computational solutions to research problems related to epigenetics and RNA biology in health and disease. They will be responsible for taking on highly interdisciplinary projects and will apply state-of-the-art open-source software for basic and advanced analysis of next-generation sequencing data. The focus will be on single-cell genomics, RNA/protein interactions, RNA translation, and chromatin organization. In addition, they will have opportunities to present research findings at conferences and network with colleagues. The ideal candidate will be highly motivated, well-organized, manage time effectively, and can work independently as well as part of a team. They will obtain fundamental, career-building exposure in bioinformatics, computational biology, and biostatistics as they develop scripts in languages such as Python and R, while using Linux/Unix and high-performance computing (HPC) to analyze genomics data.

Job Duties

• Manage and analyze CUT&TAG, RNA-seq, ATAC-seq, single-cell RNA-seq, single-cell multiomics, CLIP-seq, and ribosome profiling data.
• Interpret results by applying and/or developing appropriate statistical and/or machine learning analysis for CUT&TAG, RNA-seq, ATAC-seq, single-cell RNA-seq, single-cell multiomics, CLIP-seq, and ribosome profiling data.
• Collaborate with wet lab scientists to refine and integrate datasets, including statistical tests.
• Maintain detailed records of computational code and analyses.
• Search and evaluate scientific literature in support of research projects.
• Co-author scientific papers.
• Effectively interact with team members to make important contributions to big problems while ensuring a high standard of scientific rigor.
  

Minimum Qualifications

• Bachelor\'s degree in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.
• Four years of relevant experience.

Preferred Qualifications

• PhD in Genetics, Biology, Bioinformatics, Biostatistics, Computational Biology, Computer Science, or a related field.