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MD Anderson Cancer Center Postdoc Fellow - Radiation Oncology- Research (Dr. Butner's Lab) in Houston, Texas

The postdoctoral fellow will execute research projects under the supervision of Dr. Joseph D. Butner, a computational and data scientist in the Radiation Oncology department at MD Anderson Cancer Center, with a focus on developing skills to transition the trainee from mentored research to independent research. Research Topics include mathematical and computational modeling of cancer development and therapy for predicting therapeutic response and improving patient outcomes. Primary duties will include development and coding of mechanistic computational models of systemic and targeted therapy, statistical models, and deep learning models, authorship of peer-reviewed publications and grant applications, conference attendance to disseminate results to the scientific community, assisting the principal investigator with mentoring junior lab members, and leading collaborative projects between the research team, clinical staff, and industry partners. Successful applicants will demonstrate a successful track record of applying predictive models to measured data and effective presentation of results. Candidates with extensive data science experience are especially encouraged to apply.

This position is within a clinical department, providing a rare opportunity for computational researchers to directly interface with clinicians on a day-to-day basis to pursue improved cancer outcomes through engineered, personalized treatment strategies. The selected candidate will play an integral role in helping to spearhead the early stages of long-term research conducted at the newly developed Institute for Data Science in Oncology (IDSO) at MD Anderson Cancer Center (MDACC), will have the chance to establish their own systems and have a major impact in shaping the lab's culture, and will influence the lab's approach to science for the coming years. While working with both clinical collaborators in the Radiation Oncology department and other computational scientists in IDSO at MDACC, the postdoctoral fellow will gain valuable experience in designing predictive tools that are readily deployable to current clinical practice.

Candidates should have an interest in adapting computational and mathematical modeling approaches to integrate within the limitations of real-world clinical operations, and in overcoming the challenges that often restrict computational models to theory-generation only. Relevant skills include strong mathematical competency and rapid comprehension of new statistical methods, and experience in object-oriented programming including Python or R, with proficiency in C++ preferred. They should also be knowledgeable in building software in cluster computing (e.g., bash, cmake, working in the terminal), including compiling against linking third-party libraries in Linux environments.


  1. Autonomously perform model design, development, and deployment.

  2. Participate in the development of Python libraries for scalable deployment of deep-learning models to predict patient outcomes to support ongoing and future projects.

  3. Perform rigorous statistical analysis and verification of model outputs and predictions.

  4. Work with clinicians, residents, and other modelers to develop and use statistical and deep-learning models to guide targeted radiation therapy by identifying lesions likely to achieve therapeutic response.

  5. Work alongside IDSO leadership to establish robust data pipelines for rapid throughput of data into predictive modeling platforms.



Required: Ph.D. or equivalent doctorate


Required: Six years of experience in scientific or experimental research work (includes graduate work)

Preferred: With preferred degree, four years of required experience


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