Date Created: August 12, 2020 - 3:33pm
We are looking for an ambitious, driven post-doctoral scientist to lead computational analysis of genomics, epigenomics, transcriptomics profiles focusing on hematological malignancies and patient-derived xenografts. The work will take place in the context of a close and productive collaboration between two laboratories at Weill Cornell Medicine and in the Meyer Cancer Center: Dr. Olivier Elemento, whose group focuses on cancer genomics, precision medicine and cancer systems biology, Dr. Giorgio Inghirami who uses patient-derived xenografts to study deregulated pathways and treatment for hematological malignancies.
The group has collectively advanced the field and published hundreds of papers in the past few years in the area of genomics (Whole-exome sequencing), epigenomics (ATAC-seq and RRBS), transcriptomics (RNA-Seq) applied to problems of high biomedical relevance. The post-doctoral scientist will perform computational analyses to integrate and interpret large multi-omics genome-wide biological datasets including, generate testable hypotheses, build predictive models that will further drive experimental discovery.
In addition, the candidate will develop software and methods to help characterize and share genomics, epigenomics, transcriptomic profiles of patient-derived xenografts and help characterize their sensitivity to therapeutic agents. We are looking for a highly interactive candidate, who will be integrated into the Institute of Computational Biomedicine (ICB). The ICB hosts 6 research groups and over 100 scientists, together with a petabyte scale high-performance computing infrastructure. The ICB also has a large group of talented and experienced computational biologists with a strong focus on cancer genomics on whom the post-doctoral scientist can rely on intellectual input, support, and extensive computational resources. Applicants may want to explore the following relevant websites: Elemento Lab and Inghirami Lab.
- Lead computational analysis of Whole-Exome Sequencing, RNA-Seq, ChIP-Seq, ATAC-Seq, RRBS and WGBS data generated in hematological malignancies (primary tumors, cell lines, patient-derived xenografts), generate hypotheses regarding deregulated mechanisms, potential therapeutic targets, biomarkers of drug response, design follow-up experiments
- As needed develop novel methods and algorithms for normalization, analysis, and visualization of large multi-omics data
- Correlate/Integrate multiple omics datasets
- Collaborate closely with several other scientists in the PIs’ groups and elsewhere
- Present results at joint group meetings and other outlets, write manuscripts
A Ph.D. in Biology, Bioinformatics or Computer Science
- Strong publication record with at least one strong first author paper
- Strong background in bioinformatics with experience in analysis of next-generation sequencing data demonstrated by relevant publications.
- An ability to program in at least one widely used language (Perl, Python, Java, C++, etc.), proficiency in statistical software packages such as R / Bioconductor, ability to create compelling graphics and use state-of-the-art data visualization methods e.g. RMarkdown, Shiny, ggplot2, D3.js
Knowledge, Skills and Abilities:
- Strong focus and interest on biomedically relevant problems
- Track record of developing novel computational methodologies and publishing innovative software packages
- Demonstrated ability to lead projects and work both independently and collaboratively
- Excellent verbal and written communication skills demonstrated by a track record of publication, public speaking, and collaborative interactions.