Sr Computational Research Scientist- MA's Lab

St. Jude Children's Research Hospital•Memphis, TN

1d•$104,000 - $186,160

About The Position

The Ma laboratory in the Department of Computational Biology is seeking an experienced Senior Computational Research Scientist for the Pediatric Cancer Dependency (PedDep) project, a joint initiative between St. Jude, Dana Farber Cancer Institute, and the Broad Institute. With vast knowledge accumulated from patient tumor data, we are now characterizing cell models (cell lines and PDX models) for childhood cancers to discover novel vulnerabilities that can lead to new therapeutic targets. In this role you will analyze the genomics data from >1,000 cancer cell models to identify their driver alterations and investigate the representativeness of cell models against the mutations observed in primary tumors. You will also study the similarities and differences of driver alterations between pediatric and adult cancers. Published studies from external and internal cohorts will be compiled for the comparison. In addition to the extensive internal tools we have developed, you will develop novel tools during the investigation to generate novel analyses and to integrate new data types. You are expected to present findings in regular internal/external forums and to draft figures/manuscripts with the help of the PI and the team. Highly motivated candidates with an MD/PhD in molecular biology, computational biology, computer science, or a closely related field are encouraged to apply. The candidate would ideally have ample experience with genome and transcriptome sequencing data analysis, in particular mutation detection and functional interpretation, as well as extensive computational skills to accurately and efficiently handle large amounts of data. Candidates should be scientifically curious, rigorous, and capable of working independently.

Requirements

MD/PhD in molecular biology, computational biology, computer science, or a closely related field.
Ample experience with genome and transcriptome sequencing data analysis, in particular mutation detection and functional interpretation.
Extensive computational skills to accurately and efficiently handle large amounts of data.
Scientifically curious, rigorous, and capable of working independently.
Strong knowledge in molecular biology, genetics, genomics and statistics.
Next generation sequencing: variant calling; IGV-based variant inspection; whole-genome/exome analysis for mutations including copy number, loss of heterozygosity, structural variation, SNV/Indel; RNAseq based fusion analysis; bam/fastq operations including mapping and basic quality control; variant functional interpretation using data collected from patient cohort and molecular biology and genetics principles.
Programming: [Python or Perl or C/C++] and R
Operating system: High performance computing system, bash scripting
Office: Microsoft Excel/Word/PowerPoint

Nice To Haves

Experience leading complex research studies in a technical capacity preferred.
Experience training and guiding early-career researchers preferred.
Proven performance in earlier role/ comparable role.
Adobe Illustrator (no Photoshop)

Responsibilities

Lead computationally focused scientific research projects with little supervision from their PI.
Initiate and execute research strategies in partnership with the Principal Investigator, collaborator, and/or more experienced scientists.
Explore, identify, and propose adoption of relevant emerging scientific and technical trends in computational research; develop new methods, techniques, and procedures.
Identify, process, organize, interpret, review, and report relevant data; generate hypotheses to predict future implications based on the critical evaluation of these data.
Direct/monitor data collection.
Present research both internally and externally to multi-disciplinary audiences; draft complex manuscripts.
Provide ongoing instruction and guidance to junior-level staff and train as needed.
Perform other duties as assigned to meet the goals and objectives of the department and institution.
Maintains regular and predictable attendance.