Summary

Baylor College of Medicine has an opportunity for a Postdoctoral Research Associate position with a focus on identifying immune, inflammatory, metabolic, and epigenetic drivers of post-infectious morbidity and mortality. The study will evaluate 300 pneumonia patient participants to identify which inflammatory, immune, transcriptomic, epigenomic, and metabolic marks are associated with post-pneumonia morbidity and mortality. Single cell technology will be implemented to identify drivers of post-infectious inflammation. Excellent applicants will need a wet lab experience in immunology, flow cytometry, and cellular metabolism, and should have a strong foundation in bioinformatic analysis. (Examples of previous work includes PMID 35169026, 35256539, 32125282).

The position is intended for life science graduates from Immunology or Microbiology backgrounds, however, a graduate with background in Computer Science or Computational Biology will also be considered. The successful candidate will receive training in analyses of single-cell and bulk-tissue multi-omics data and be expected to participate in multiple projects involving design, implementation and integration of large-scale datasets and data processing pipelines

Job Duties

• Implements measurements of inflammation, host immunity, and cellular metabolism from ex vivo PBMCs and plasma from patients recovering from pneumonia, HIV, or Tuberculosis.
• Implements and analyzes single cell RNA-Sequencing, single cell ATAC-Seq, CITE-Seq, as well as bulk RNA-Seq, Proteomics, Metabolomics, and Lipidomics datasets, generated from pneumonia tuberculosis patient cohorts with rich clinical data.
• Conducts advanced modeling of post tuberculosis lung disease risk using approaches including generalized linear models and deep learning.

Minimum Qualifications

• Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Ph.D. in Biology, Immunology, Computer Science, or Bioinformatics.
• Experience in epigenetics or gene regulation is a plus, and experience with statistical analysis tools such as R or Python is recommended (successful candidates will be expected to pass a basic programming test in R or Python).
• Excellent written and verbal English skills, strong communication and interpersonal skills, and must be capable of working with large collaborative teams.