Research Investigator - Radiation Oncology Research Department

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.

The primary purpose of the Research Investigator is to assist the Principal Investigator and other Faculty members with scientific research projects. Learns and adapts techniques for use in ongoing research, plans and assists training and research work activity for research personnel, and provides guidance and training to early-stage researchers within the lab. Supervises use of laboratory equipment, implements safety procedures, maintains records, compiles, writes and submits project results to superiors. Participates in planning and preparation of applications for grants and other research support pipelines. Reads and understands current scientific literature.

The Research Investigator 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 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, 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 successful track-record of applying predictive models to measured data and effective presentation of results. 

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 the practical usability of computational models. Relevant skills include strong mathematical competency and rapid comprehension of new statistical methods, and experience in scripting in languages such as Python, Mathematica, MATLAB, or R (proficiency in C++ preferred). Experience in building software in cluster computing (e.g., bash, cmake, working in the terminal), including compiling against third-party libraries in Linux environments, 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!

KEY FUNCTIONS

1. AUTONOMOUSLY PERFORM MODEL DESIGN, DEVELOPMENT AND DEPLOYMENT. INSTRUCTS AND ASSISTS OTHER LAB MEMBERS ON MODEL DEVELOPMENT AS NEEDED.

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.

6. TRAINING AND SUPERVISION OF OTHER RESEARCH PERSONNEL ON TECHNIQUES AND COMPUTATIONAL AND MATHEMATICAL APPROACHES. CRITICALLY REVIEWS RESEARCH CONDUCTED BY OTHER LAB MEMBERS TO VERIFY SCIENTIFIC INTEGRITY AND PROVIDE CRITICAL FEEDBACK.

7. ASSIST IN WRITING OF SCIENTIFIC PAPERS FOR PUBLICATION, GRANT APPLICATIONS AND PRESENTATIONS AT SCIENTIFIC MEETINGS

8. OTHER DUTIES AS ASSIGNED