Computational Scientist - Dr. Pavan Bachireddy's Laboratory

Houston, Texas
February 24 2021
Health Sciences
Organization Type
The University of Texas MD Anderson Cancer Center in Houston is one of the world's most respected centers focused on cancer patient care, research, education and prevention. It was named the nation's No. 1 hospital for cancer care in U.S. News & World Report's 2018 rankings. It is one of the nation's original three comprehensive cancer centers designated by the National Cancer Institute.

The primary function of the Computational Scientist is to provide analysis and develop algorithms and software for clinical and scientific problems. This position will impact clinical and scientific research projects by developing programs and applications tailored to meet specific research objectives.

Key Functions

Data Management: **Develop/modify/create pipelines for interpreting data from single-cell (and/or bulk data) experiments from publicly available and locally developed tools. **Ensure data organization.

Data Analysis: **Independently design computational experiments, analysis approach and results interpretation. Prioritize and manage multiple projects in a timely and resource-effective manner. Report research findings (oral and written) at internal, local and national meetings. **Apply advanced statistical methods, simulation models, and skilled programming as needed. **Remain up-to-date on immunogenomic tools.

Marginal Assistance: **Advises and assists users and other personnel in analyzing, defining and resolving computer problems. **Other duties as assigned.

Recruitment Interest

Recruiting a forward thinking and innovative computational scientist excited to study co-evolving leukemic-immune interactions within the tumor microenvironment that are relevant for human cancer immunotherapy.

The candidate should have a strong foundation in computational biology (or related discipline) and an understanding of molecular/cancer or immuno- biology. The primary focus is the analysis of high-dimensional data from high-throughput profiling technologies (bulk and single cell) such as whole exome sequencing and a range of single cell approaches (e.g. RNA/TCR/ATAC/CITE-seq). Comfort and ease with various modelling and machine-learning approaches are essential. The candidate will apply technical expertise and experience to independently plan, coordinate, design, supervise and carry out research projects. Compiles, writes and submits reports to PI. The candidate will work with experimental scientists within the laboratory to design scientific strategy and develop innovative tools.

The lab uses the latest advances in unbiased, single cell profiling techniques combined with innovative bioinformatic methods to uncover the molecular and cellular circuitry governing responses to immunotherapies in hematologic malignancies. In vitro and in vivo genomic screens are critical approaches to functionally validate our findings.

: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Physics, Applied Mathematics or related field.

Preferred: Master's degree or PhD with a concentration in Science, Engineering or related field. Master's degree (M.S.) or PhD in Computational Biology, Computer Science, Engineering, Applied Mathematics, Biostatistics or a related discipline with BS/MS in Immunology, Cancer Biology or a related discipline.

: Five years experience in scientific software development/analysis. With preferred degree three years experience required.

Preferred: Proficiency in scripting/statistical computing. Experience manipulating datasets/high performance computing. Familiarity with data normalization/analysis of batch effects. Development of statistical algorithms and comprehensive assessments for analysis. Collaboration with bench biologists, next-generation sequencing analytics, pathway/network analysis, and transcriptional regulator networks.

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.

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