A Lead Bioinformatics Analyst position is available in the field of pharmacogenomics in the Savic laboratory. The primary research focus of the Savic laboratory involves studying the gene regulatory architecture of pediatric leukemia and genomic responses to antileukemic agents in order to define how the noncoding portion of the human genome impacts chemotherapeutic drug response, chemotherapeutic drug resistance and leukemia relapse. To address these critical questions, the Savic laboratory uses functional genomics (ChIP-seq, ATAC-seq, RNA-seq, Hi-C, etc.) to map cis-regulatory elements and noncoding sequence variants in primary leukemia cells from patients and further applies high-throughput approaches (STARR-seq, MPRA, CRISPR screening, etc.) to functionally characterize their impact on gene regulation and pharmacological phenotypes using both in vitro and ex vivo models. The long-term goal of the Savic laboratory is to gain a better understanding of the genetic underpinnings of chemotherapeutic drug resistance and relapse in pediatric leukemia.
The successful candidate will be responsible for analyzing and integrating orthogonal genomic datasets in order to infer the pharmacogenomic impact of cis-regulatory elements and noncoding sequence variants. To meet these tasks, the candidate will be responsible for implementing, building and managing analytical pipelines for collaborative projects within the laboratory and beyond the laboratory.
- Bachelor’s degree is required.
- Master’s degree or PHD is preferred
- Six (6) years of relevant experience is required.
- Four (4) years of relevant experience may be acceptable with a Master’s degree.
- No experience may be acceptable with a PHD in Computer Science or Bioinformatics, with a background in the biological sciences.
- Experience in programming (Python, Java, C/C++, perl or other programming/scripting languages) under linux/unix environment is required.
- Experience with and the ability to deal with a wide range of users is required.
- Experience of independent data analyses and project management is required.
- End user support and training experience is required.
- Experience with open source software development preferred.
- Experience in development of algorithms, statistical methods or scientific software preferred.
- Experience in next-generation sequence analysis or imaging analysis is preferred.
- Experience in working with high-throughput data sets in a highly competitive environment is preferred.
- Experience in working in a team project is preferred.
- Cross training in biological sciences (e.g. genomics, genetics, transcriptomics and epigenetics) preferred
- Scripting experience using a statistics package such as R, S-Plus or SAS preferred.
- Experience in personnel management preferred.
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