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Postdoctoral Associate Position in Computational Genomics
Company Information
The laboratory of Jihoon Kim at the Section of Biomedical Informatics and Data Science, Yale School of Medicine is seeking a computational genomics/bioinformatics postdoctoral associate. The research program in this lab focuses on computational genomics in application to human disease using registries and biobanks including All of Us Research Program, Million Veterans Program, and UK Biobank, either a single biobank or cross-biobanks using federated learning. Current research projects aim to identify genetic variants/genes associated with disease traits (susceptibility/treatment response/progression) toward personalized medicine and unravel disease pathogenesis through analyses of different types of omics data including but not limited to whole genome sequencing, messenger RNA-seq, cell-free RNA-Seq, and proteomics (e.g., Somascan) obtained from the same patients along with linked clinical phenotype.
The Kim lab is well funded by NIH and private sources. The successful candidate will have a great opportunity to publish several high-quality papers in collaboration with top-notch investigators during his/her stay. The successful candidate will receive comprehensive and personalized training in research and career development and will have extensive opportunities for independent and collaborative research.
Under the supervision of the principal investigator (Dr. Jihoon Kim), the successful candidate will
#1. work on study design, data collection, data management, analysis pipeline development, data analysis, and results interpretation, as well as manuscript writing
#2. develop novel bioinformatics methods
#3. publish high-quality papers reporting on methodological and biological advances
#4. present at conferences
#5. participate grant proposal preparation
#6. collaborate with other researchers
#7. teach/mentor other lab members
#1. Ph.D. in bioinformatics, computational biology, computer science, statistics, genetics or related field required by the start date
#2. Demonstrated ability to design, implement, and apply for the analysis of high-throughput omics data
#3. Demonstrated expertise in implementing bioinformatics methods and software tools
#4. Demonstrated ability to effectively communicate computational biology problems to clinicians, peers, subject matter experts and investigators
#5. Independent, highly motivated and highly collaborative with ability to work in a team environment
#6. Strong communication skills in English (spoken and written)