A postdoctoral position is available in Dr. Bing Zhang’s laboratory (www.zhang-lab.org) to work on computational proteomics, immunopeptidomics, and proteogenomics 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 participate in both method and tool development and biological applications.
The position offers an excellent opportunity to conduct research in a supportive and stimulating environment, and to collaborate with bioinformaticians, biostatisticians, computer scientists, biologists, and clinicians.
ESSENTIAL FUNCTIONS AND DUTIES
• 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.
• Performs other job-related duties as assigned.
• Ph. D. in bioinformatics, proteomics, computer science, biostatistics, mathematics, cancer biology, or a related field.
• Experience in proteomics, and/or proteogenomics 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
• 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
Email Prof. Bing Zhang (bing.zhangATbcm.edu)