Postdoctoral Associate

A computational biology postdoctoral position is available in Dr. Bing Zhang’s laboratory to work on proteomics and proteogenomics data analysis with application to precision oncology. Our research is funded by the National Cancer Institute (NCI), the Cancer Prevention and Research Institute of Texas (CPRIT), and the McNair Medical Institute at The Robert and Janice McNair Foundation. We develop methods and tools for the analysis, interpretation, and dissemination of proteomics and proteogenomics data. We also participate in several large collaborative projects that generate multidimensional omics data at DNA, mRNA, protein, and clinical phenotype levels from human tumors, patient-derived xenografts (PDXs), and cancer cell lines. As one example, we led/co-led several CPTAC cancer proteogenomic studies that were published in Nature, Cell, and Cancer Cell. The candidate will

Job Duties

The candidate of this position is expected to independently carry out research projects in or related to the abovementioned field.

• Designs and develops efficient and scalable databases for the storage of multi-omics data as well as relevant knowledge.
• Implements data quality control measures and data integration strategies to ensure data accuracy and consistency.
• Optimizes data retrieval and management processes for rapid access and analysis.
• Develops user-friendly web applications to facilitate data retrieval and exploration by biologists and clinicians.
• Designs interactive and visually appealing data visualization tools to enhance data interpretation.
• Collaborates with multidisciplinary teams to integrate data from various sources, ensuring compatibility and reliability.
• Maintains updated knowledge of relevant data standards and ontologies in the field of cancer research.
• Creates clear and comprehensive documentation for databases and web applications.
• Provides training and support to end-users to ensure effective utilization of developed tools.
• Collaborates with researchers and clinicians to understand their specific data requirements and integrate their feedback into the development process. 
• Stays up-to-date with the latest advancements in cancer research to align database and application development with emerging trends.
• Publishes methods, software and application papers.
• Develops novel proteomics and proteogenomics data analysis methods and algorithms.
• Researches and evaluates newly published methods and algorithms for integrating into our existing proteogenomics data analysis tools.
• Applies established tools and methods to cancer proteomics, immunopeptidomics, and proteogenomics studies.
• Publishes methods, software and application papers.
• Provides technical guidance, work direction and training to other lab members on areas of expertise. 

Minimum Qualifications

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

Preferred Qualifications

• Ph. D. in bioinformatics, computer science, biostatistics, mathematics, cancer biology, or a related field.
• Experience analyzing immunopeptidomics data
• Experience analyzing phosphoproteomics data and/or other post-translational modification data
• Experience with cancer proteogenomics studies
• Knowledge about molecular biology and cancer biology
• Experience with deep learning algorithms and frameworks
• Experience with Amazon Web Services
• Experience with NextFlow and Docker containers
• Experience in proteomics and/or multi-omics data analysis as demonstrated by peer-reviewed publications and/or software packages.
• Knowledge about statistics and machine learning algorithms.
• Strong programming skills (R and Python/Perl/Java)
• Programming in UNIX/LINUX environment
• Strong presentation skills and written/verbal communication skills

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

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