Postdoctoral Associate- Single- Cell and Data Science

The position is intended for Computer Science, Computational Biology, or life science graduates transitioning to a data science and bioinformatics career.  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.

• Analyzes single cell RNA-Sequencing, single cell ATAC-Seq, CITE-Seq, as well as bulk RNA-Seq, Proteomics, Metabolomics, and Lipidomics datasets, generated from brains of HIV patient cohorts with rich clinical data.
• Conducts advanced modeling of cognitive ability scores using approaches that include generalized linear models and deep learning. 

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

• 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 Python).  
• Candidates must have a  Ph.D. in Computer Science, Bioinformatics, or biology, as well as a strong background in statistics, and familiarity with large data sets such as proteomics or sequencing.
• Must be highly proficient in spreadsheets and generating reports.
• Excellent communication skills is a plus.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.