A postdoctoral research associate position is immediately available in the lab of Dr. Jinghui Zhang, Chair of the Department of Computational Biology, for a highly motivated candidate to develop a visualization tool for analyzing genetic association with clinical features of pediatric cancer survivors. The candidate will be involved in developing a predictive model of acquiring secondary cancer in pediatric cancer survivors. The study is an ongoing collaboration between the Zhang lab and the lab of Dr. Yutaka Yasui, Member (Professor), Department of Epidemiology and Cancer Control. Both the genomic data and phenotype type data will be incorporated in the study. The Zhang lab will provide training and mentoring on genomics, visualization, product development and project management. The fellow will have opportunities to interact with leaders in the fields of pediatric cancer and translational research within and outside the institution. Innovative research leading to high-impact scientific publication is highly encouraged and will be supported by the lab’s research infrastructure. The appointment will be for 2-5 years, depending on the candidate’s goals, qualifications, and productivity.
Recognized as a world leader of genomic research in pediatric cancer, the Zhang lab has led the characterization of the genomic landscape for over 20 subtypes of pediatric cancers with high-impact publications in Nature, Nature Genetics, Nature Methods, JAMA, Cancer Cell, and NEJM in the last five years. The lab has a well-established track record of developing and publishing novel and high-impact analytical and visualization tools for cancer genomic research. Research in the lab is facilitated by access to the wealth of high-quality data, state-of-art high performance computing facility, robust analytical pipelines, latest laboratory technology and scientific expertise in genomics, cancer biology, and mathematics and computer science.
St. Jude provides a highly interactive and supportive environment for researchers’ career development.
The successful candidate will have good training in human genetics and statistical analysis. Additional training and experience in bioinformatics and cancer biology are preferable. The candidate is expected to be a critical thinker, a quick learner for new analytical approaches and capable to apply or develop novel computational methods for solving complex problems. Candidate must have a doctoral degree (PhD or MD), an excellent publication record and great communication skills.
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