Bioinformatics/Machine Learning/Biomarker Discovery Postdoctoral Fellow
H. Lee Moffitt Cancer Center
Dr. Xiaoqing Yu’s Lab within the Department of Biostatistics and Bioinformatics, and Dr. Roger Li from Genitourinary Oncology at the H. Lee Moffitt Cancer Center, are jointly seeking a highly motivated, independent, and collaborative postdoctoral research fellow interested in conducting exciting inter-disciplinary projects in multi-omics data analysis and cancer biomarker discovery. The postdoctoral research fellow will also be co-mentored by Dr. Xuefeng Wang from Department of Biostatistics and Bioinformatics. The position will remain open until filled.
·The position is essential for development of comprehensive tools benefiting basic to clinical research through identification of novel biomarkers to treat cancer and the improved treatment stratification of cancer patients.
·The postdoctoral research fellow will enjoy a close working relationship with bioinformaticians, statisticans, clinicians, translational researchers, as well as bench scientists to establish a well-rounded multidisciplinary team.
·Access will be provided to curated clinical samples from practice changing clinical trials to further the understanding of the mechanisms of action of the investigational agent(s) and treatment resistance.
·Access will be provided to prospective longitudinal liquid biopsy samples to conduct biomarker discovery work.
·Outstanding mentorship from expert faculty with wide-ranging funded research programs including T32 Training Grants.
·You will be encouraged and supported to apply for training grants.
The Ideal Candidate:
·Research background/experiences in Bioinformatics, Statistics, Computational Biology, Machine Learning, or Computer Science.
·A highly motivated and independent researcher with a strong quantitative scientific background.
·Programming experience in statistical program R and/or scripting languages such as Perl/Python on Unix/Linux systems.
·Experience in cancer genomics is not required but the ability to learn new knowledge is highly desirable.
·Excellent communication and writing skills.
·Experience of integration of multi-omics data such as WES, RNA-seq, metabolomics, proteomics, etc, is preferred.
·Develop and extend machine learning methods for big cancer Omics data such as single-cell omics data and spatial transcriptomics data.
·Develop bioinformatics pipelines for analyzing high dimensional immunological data.
·Develop novel visualization tools for interpreting big cancer Omics data.
·Discover new predictive biomarkers for cancer prognosis.
·Collaborate on a variety of cancer and bioinformatics research projects.
Credentials and Qualifications:
PhD in Bioinformatics, Statistics/Biostatistics, Applied Mathematics, Data Science, Computer Science, or related fields.
How to Apply: Interested applicants should send a single PDF file that includes a cover letter summarizing their research training and accomplishments, a personal statement of scientific interests and goals, current CV with recent publications, and contact information for three references to Dr. Xiaoqing Yu (email@example.com).