Bioinformatician - Genomic Medicine

The mission of The University of Texas M. D. Anderson Cancer Center is to eliminate cancer in Texas, the nation, and the world through outstanding programs that integrate patient care, research and prevention, and through education for undergraduate and graduate students, trainees, professionals, employees and the public.

Ideal candidate for the Bioinformatician position will have working experience in mining genomic and clinical data.  Experience in pattern recognition/machine learning, mathematical/statistical modeling, network analysis and experience in data integration, data mining, NGS data analysis (mutations, structural variations, and expression).  Proficiency in at least one programming language such as R, C/C++, Perl, Python, or JAVA.

As part of M. D. Anderson’s Moonshots program, patients’ clinical and genomic data will be collected and integrated to create increasingly large data repositories that will be mined to drive translational research and ultimately improve patient outcome. Working closely with clinical colleagues, the Bioinformatician positions within the Department of Genomic Medicine provide the opportunity for the candidate to participate in and contribute to all aspects of mining large scale data sets related to patients, exploring and understanding the complex interactions of genotype and clinical phenotype, formulating and validating hypothesis, and identifying prognostic and predictive models as well as potential targets for treatment and drug development.

KEY FUNCTIONS

·        Extract and integrate internal and public genomic and clinical data to produce standardized data sets that can be distributed within M. D. Andersons’ computing environment and used by clinicians and researchers.   

·        Develop software modules to regularly perform standard data analysis routines in an automated fashion and provide visualization tools for clinicians and researchers to explore the results. 

·        Systematically explore and mine multi-dimensional data to validate experimental findings or formulate hypothesis to provide directions of further studies.

·        Identify issues of practical or theoretical importance and drive to solutions through innovative mathematical/computational approaches. 

·        Evaluate existing algorithms and develop new algorithms and user friendly tools that can be deployed to MDACC or larger research communities.

·        Work closely with clinicians and biologists to provide customized bioinformatics/computational support throughout their studies.

·        Work with bioinformaticians, IT personnel, and other researchers to respond to new technologies.

Working Conditions

Laboratory environment

Physical Demands

Indicate the time required to do each of the following physical demands: