Postdoctoral Fellow- Computational Biology

Join to apply for the Postdoctoral Fellow (Computational Biology) - Butner Lab role at Komen Graduate Training Program UT MDACC

The postdoctoral fellow will execute research projects under the supervision of Dr. Joseph

D. Butner, a computational biologist and data scientist in the Radiation Oncology department at MD Anderson Cancer Center, with a focus on developing crucial skills to support the postdoc's transition from mentored research to independent investigator. Research topics include mathematical and computational modeling of cancer development and therapy for predicting therapeutic response and improving patient outcomes. Primary duties will include the development, coding, and data analysis of mechanistic computational models of systemic and targeted therapy, which may also include statistical or machine learning models, authorship of peer-reviewed publications and grant applications, conference attendance to disseminate results to the scientific community, and assisting the principal investigator with mentoring junior lab members.

Members of the Butner laboratory also have the exciting opportunity to lead collaborative projects between the research team, clinical staff, and industry partners. Successful applicants will demonstrate a track record of applying predictive models to measured data and effective presentation of results.

Candidates with the following backgrounds are especially encouraged to apply, but all applications will be reviewed and considered:

• Applied mathematics
• Physics
• Engineering
• Computational biology
• Computer science
• Biology with a heavy focus on mathematics

This position is within a clinical department, providing a rare opportunity for computational researchers to interface with clinicians on a day-to-day basis to pursue improved cancer outcomes through engineered, personalized treatment strategies. The selected candidate will help spearhead early-stage research at the Institute for Data Science in Oncology IDSO at MD Anderson Cancer Center, establish their own systems, and influence the lab's approach to science for the coming years.

While working with clinical collaborators in the Radiation Oncology department and other computational scientists in IDSO at MD Anderson, the postdoctoral fellow will gain experience in designing predictive tools that can be deployed in 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 challenges that restrict practical usability of computational models. Relevant skills include strong mathematical competency and rapid comprehension of new statistical methods, and experience in scripting languages such as Python, Mathematica, MATLAB, or R (proficiency in C++ preferred).

Experience building software for cluster computing (bash, cmake, working in the terminal, Linux) is preferred but not required.

Whether you're experienced in all these areas or eager to learn, we provide a supportive environment to help you thrive and grow as a researcher. Join us in our mission to improve cancer care through innovative computational approaches!

• Autonomously perform model design, development and deployment.
• Participate in developing python libraries for scalable deployment of models to predict patient outcomes to support ongoing and future projects.
• Perform rigorous statistical analysis and verification of model outputs and predictions.
• 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.
• Work alongside IDSO leadership to establish robust data pipelines for rapid throughput of data into predictive modeling platforms.

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

• Education:
  
  Required:
  
  Ph.D. or equivalent doctorate
• Experience:
  
  Required:
  
  Six years…