The Surgical Oncology Department is recruiting highly intelligent and motivated individuals to participate in cutting-edge research focusing on sarcoma genomics and immuno-oncology. This individual will be tasked with supporting computational analyses for ongoing experimental projects in the new laboratory of Dr. Emily Keung and co-supervised by Dr Kadir Akdemir at MD Anderson Cancer Center. The laboratory is a mixed wet/dry lab environment focused on the development of novel model systems and h... more details
SUMMARY
The Surgical Oncology Department is recruiting highly intelligent and motivated individuals to participate in cutting-edge research focusing on sarcoma genomics and immuno-oncology. This individual will be tasked with supporting computational analyses for ongoing experimental projects in the new laboratory of Dr. Emily Keung and co-supervised by Dr Kadir Akdemir at MD Anderson Cancer Center. The laboratory is a mixed wet/dry lab environment focused on the development of novel model systems and high throughput methods for dissecting the genetic mechanisms and immuno-oncology of soft tissue sarcomas (mesenchymal tumors which can arise anywhere in the body). The successful candidate will use advanced technologies and instrumentation for cancer cell genome characterization, will have solid molecular biology experience, and is willing to acquire experience in the analysis of maturing technologies.
JOB SPECIFIC COMPETENCIES Analyze Next-generation Sequencing DataAssists in the analysis and development of pipelines, algorithms and software for the analysis, exploration, and visualization of data generated using whole genome sequencing, bulk and single-cell RNA-seq, ATAC-sequencing, ChIP-sequencing, and chromatin conformation capture sequencing (e.g., Hi-C and similar methods) in a timely fashion. Runs somatic mutation, copy number and transcriptional alteration pipelines on matched tumor/normal pairs whole exome/genome and RNA-seq data. Runs clonality estimation and mutational phylogeny inference tools. Performs single-point and serial analysis of single-cell RNA-seq, ATAC-seq, CITE-seq and TCR/BCR-seq data. Creates pipelines comprising a wide-ranging suite of in-house and external immune deconvolution, HLA inference, neoantigen prediction, T- and B-cell repertoire analysis software. Writes custom scripts to improve immunogenic methods developed in the lab. Package tools using Docker and Conda applications
Proficiency in Programming Languages/ System, Development and TroubleshootingWith direction, develops and maintains software tools and infrastructure for resolving specific problems. Adapt to new technologies and find solutions to related academic programs. Demonstrates extensive knowledge and familiarity with UNIX-like computing environment and high-performance computing resources. Proficiently use Python and R to develop extensible, well-documented, and user-friendly workflows (Snakemake and others) for analysis of data generated by laboratory members.
Support Ongoing Research ProjectsCollaboratively works with wet lab members to develop procedures and analytical frameworks. Reads literature and confers with superiors regarding new procedures and modify them according to the needs of the project. Ability to search and review the scientific literature for the purpose of developing computational pipelines and supporting the completion of grant applications. Demonstrates flexibility in assisting closely related projects being pursued by other labs in the Genomic Medicine Department.
Maintains Good Lab Practices per the institutional PoliciesContributes to project team. Employ safe laboratory practices. Maintains research records and laboratory notes. Interacts closely with other research staff across institutional functional teams.
Other duties as assigned
Onsite Presence: Is Required
WORKING CONDITIONS
Frequency
Deadlines Hazardous Chemicals and Materials Operating Equipment Sedentary Environment Exposure to blood, bodily fluids, and/or tissue
Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.
Preferred Education:
PH-D or Master's degree in Genetic/Genomics or Computational Biology.
Required Experience:
Two years experience in scientific software or industry development/analysis.
Preferred Experience:
Computational biology expertise and ability to build pipelines and perform analyses of big datasets, including tumor and cancer cell line bulk and single-cell sequencing datasets, wet-lab (molecular biology and/or immunology) techniques (especially DNA/ RNA biology), excellent skills in scientific communication and collaboration, ability to think independently and acquire/learn new skillsets. Effective verbal communication skills.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
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