Postdoctoral Fellow - Biostatistics

The Department of Biostatistics at UT MDACC has one post-doc position open for biostatistics methodology research and high-throughput data analysis applications. The focus is research and publication. The primary research area can encompass: (i) developing and applying novel statistical and computational methods for the analysis of omics data from various sources such as high-throughput proteomic, genomic, sequencing, transcriptomic, and imaging data, with particular emphasis on developing integrative and flexible models that incorporate both biological knowledge and empirical structures;

(ii) developing novel statistical and machine learning methods for the analysis of proteomics data with focuses on cancer research. Specific research areas include the integration of metabolites and proteins for early detection and risk assessment of cancer. The fellow will gain experience in cutting-edge analysis of "big data" and have the opportunity to publish in high-impact biostatistics, bioinformatics and health research journals.

The fellow will work under the supervision of Drs. Ehsan Irajizad, Kim-Anh Do and Sam Hanash on challenging and important clinical and biological projects that involve complex statistical modeling, data analysis and computation.

All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.

The candidate will learn on areas include statistical theory and application in cancer proteomics/genomics;
Obtain expertise in the integration of metabolites and proteins for early detection and risk assessment of cancer;
Gain experience in cutting-edge analysis of "big data" and novel machine learning algorithms;
Acquire extensive experience in R, R-Shiny, Python, and other programming languages/environments.

We seek a highly motivated individual with a Ph.D. in biostatistics/bioinformatics or a related quantitative field such as computer science, engineering, or quantitative computational biology.

Interest or background in computer-intensive methodology, bioinformatics, genomics, and proteomics is preferred.

Applicants must have strong training in statistics and excellent programming skills, in particular R/Python/Matlab and preferably one lower-level computer language such as C or Fortran, and interest in the application of state-of-the-art statistical methods to complex data. Experience with high-performance computing and linux system is a plus. Expertise or skills in any of the following areas are desirable: analysis of high-dimensional data with missing values, mass-spectrometry, and biomedical data analysis.

MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition

Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

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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