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 the cutting-edge analysis of "big data" and have the opportunity to publish in high-impact biostatistics, bioinformatics, and health research journals.

The post-doc 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.

LEARNING OBJECTIVES

The candidate will learn in areas including 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 the cutting-edge analysis of "big data" and novel machine learning algorithms; Acquire extensive experience in R, R-Shiny, Python, and other programming languages / environments.

ELIGIBILITY REQUIREMENTS

We seek a highly motivated individual with a 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.

POSITION INFORMATION

MD Anderson follows the NIH stipend levels as outlined by the "Kirchstein - NRSA". This full-time trainee position will provide a salary between $56,484 to $68,604, dependent upon the years of postgraduate experience.

MD Anderson offers compensated trainees :

• Paid medical benefits (zero premium) starting on first day for trainees who work 30 or more hours per week
• Group Dental, Vision, Life, AD&D and Disability coverage
• Paid Education Vacation and Sick Leave
• Paid institutional holidays, wellness leave, childcare leave and other paid leave programs
• Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans
• Employer paid life, AD&D and an illness-related reduced salary pay program
• Health Savings Account and Dependent Care Reimbursement flexible spending accounts
• Fertility benefits
• State of Texas longevity pay
• Extensive wellness, fitness, employee health programs and employee resource groups

FACULTY MENTOR

Dr. Kim-Anh Do, Dr. Samir Hanash