Associate Computational Scientist

Associate Computational Scientist

JOB SPECIFIC COMPETENCIES

Specific data analysis skills and knowledge competencies

- Previous experience working with large-scale genomics datasets (whole exome sequencing, RNA, TCR sequencing; bulk and/or single cells data) is desired
- Background in genomics, bioinformatics, or biostatistics
- Knowledge of cancer immunology is desired
- Proficiency in statistical and computational programming languages (in particular R and Python)
- Experience in command line interface and Linux environment
- Strong oral and written communication skills
- Develop innovative statistical/computational approaches to molecular data analysis
- Assist in the generation of tools for manipulating and preparing data for visualization
- Help maintain, support, and document shared tools, code base, and data sets, with opportunities to explore deeper and more complex software design problems, or bioinformatic and analytic aspects of predictive modeling.

Execute and participate in scientific research projects

Related projects and responsibilities will include:
- Whole-genome sequencing, bulk and single cell RNA sequencing, and bulk and single cell TCR-sequencing of tumor and/or blood samples
- Integrating diverse research and clinical datasets generated from patient samples using different platform and techniques
- Studies of resistance to existing and emerging cancer therapies using patient-derived data
- Studies of tumor evolution and progression and how it relates to the tumor-immune microenvironment using longitudinal patient samples
- Studies of cancer immunotherapies to develop predictors of response
- Support and conduct research within a translational and clinical research environment that involves curating and storing multidisciplanry data.
- Develop an understanding of cancer biology and cancer immunology key mechanisms

The goals of this work consist in integrating and analyzing bulk and/or single cell genomic, transcriptomic, and TCR repertoire data to determine the effects of genomic alterations, gene expression changes, and the tumor-immune microenvironment on clinical outcome. These new data will help identify novel approaches for personalized care in oncology or provide support for new methods in clinical decision-making, biomarkers for rational drug development, and new insights into cancer biology and cancer immunololgy through innovative analyses.

Work closely with other staff members

- Maintain good working relationship with other researchers and technicians
- Train and supervise other personnel in data analysis pipelines, bioinformatic techniques, and maintain internal databases

Other duties as assigned

Bachelor's degree in Biomedical Engineering, Electrical Engineering, Physics, Applied Mathematics or related field. Education Preferred: Master's degree in Biomedical Engineering, Computational Biology, Bioinformatics, Genetics, Statistics or a related field. Three years experience in scientific software development/analysis. With preferred degree, one year of required experience.

The following is a list of highly desirable experience for this position;

1. Ability to apply software tools to perform data analysis and interpret the biological significance from results in cancer research.
2. Ability to work as a member of an interdisciplinary team to discover and disseminate knowledge for enhancing cancer research and patient management.
3. Experience in working with laboratory scientists to interpret genomic data analysis.
4. Experience working with large scale genomic data and basic immunology knowledge

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