Summary

The lab of Dr. Kyle Eagen (www.eagenlab.org) at Baylor College of Medicine focuses on elucidating how DNA folds within cells and how DNA misfolding relates to human disease. Baylor College of Medicine is widely recognized for its exceptional, innovative, and collaborative research environment, and is investing significant resources in expanding interdisciplinary research in the computational, genomic, cellular, and molecular bases of human health and disease. Dr. Eagen’s lab is dedicated to applying state-of-the-art computational strategies to make important contributions to biomedicine and to educate and train the next generation of computational biologists. The lab is located in the Texas Medical Center, the largest biomedical complex in the world, immediately adjacent to Houston’s vibrant Museum District and Hermann Park.

A Research Associate position is available immediately in the laboratory of Dr. Kyle Eagen. The individual will identify and implement computational solutions to research problems related to genome 3D structure in both health and disease. They will be responsible for taking on highly interdisciplinary projects and key functions in this endeavor, including applying state-of-the-art open-source software for basic and advanced analysis of next-generation sequencing data with an emphasis on high throughput chromosome conformation capture (Hi-C) data. They will also analyze epigenetics and transcriptomic datasets. They will work closely with Dr. Eagen to develop cutting-edge computational tools as the lab expands into new research areas.

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 have a background in bioinformatics, computational biology, and/or biostatistics and have experience developing scripts in languages such as Python and/or R. The Research Associate must be able to use Linux/Unix to autonomously analyze data using high performance computing (HPC) workload managers and job schedulers.  
 

This role will involve occasional weekend and evening work hours.

Job Duties

• Manages, plans for, and analyzes genomics data:
  • Maintain and expand upon existing computational pipelines for Hi-C, ChIP-seq, CUT&RUN, and RNA-seq
  • Interpret results by applying and/or developing appropriate statistical and/or machine learning analysis for Hi-C, ChIP-seq, CUT&RUN, and RNA-seq
  • Collaborate with wet lab scientists to interpret and refine Hi-C, ChIP-seq, CUT&RUN, and RNA-seq analysis, including statistical tests
  • Develop novel computational and visualization tools to further the analysis and interpretation of Hi-C data
• Administrative
  • Prepare reports, charts, and graphs for presentations and publications
  • Maintain detailed records of computational code and processes
  • Manage next-generation DNA sequencing data
  • Search and evaluate scientific literature in support of research projects
  • Co-author scientific papers
• Effectively interact with team members to make important contributions on big problems while ensuring a high standard of scientific rigor

Minimum Qualifications

• Master's degree in Basic Science or a related field.  Experience in lieu of degree will not be accepted.
• Three years of relevant experience typically as a Research Assistant, Research Technician or Postdoctoral Fellow/Associate.

Preferred Qualifications

• Master's degree in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Genetics, Biology or a related field
• Demonstrated experience in:
  • Infrastructure: Linux Operating System and PBS or SLURM cluster-based computing
  • Programming Languages: Python, Shell Scripting, R
  • Analytical: critical thinking, data modeling, problem solving, troubleshooting
• Demonstrated ability working with open-source bioinformatics software
• Experience in bioinformatics analysis of RNA-Seq, ChIP-Seq and/or Hi-C data preferred
• A record of taking initiative to solve problems and working to high-quality standards
• Attention to detail and accurate record keeping
• Ability to multitask, work and learn independently, and be self-motivated