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Research Assistant II - Radiation Physics - Research
The Radiation Planning Assistant (RPA) initiative at MD Anderson Cancer Center advances global access to high‑quality radiation therapy by developing AI‑driven tools that automate contouring and treatment planning. The team supports clinics worldwide, particularly in low‑ and middle‑income countries, by building scalable, clinically relevant software solutions that enhance cancer care delivery.
The Research Assistant supports the development, testing, and documentation of software tools and machine learning models used within the RPA platform. This role works closely with scientists, engineers, and international partners to ensure tools meet clinical needs. The position also provides opportunities for academic growth through publications and scientific presentations.
The ideal candidate holds a bachelor’s or master’s degree in computer science or a related technical field and brings experience in programming, preferably Python. Experience with medical imaging, medical physics, or machine learning is highly valued. Candidates with online coursework or certifications in Python are encouraged to apply. The ideal individual is collaborative, detail‑oriented, and demonstrates experience contributing effectively within a team environment. Strong technical writing skills and interest in scientific communication strengthen the candidacy.
Hourly breakdown of salary range: Minimum $21.63 – Midpoint $27.16 – Maximum $32.69
Why Us?
• Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.
• Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.
Key Job Functions:
• Assist with development and testing of software tools for medical image analysis and treatment planning.
• Support data organization, preprocessing, and documentation following RPA standards.
• Contribute to code quality assurance, testing, and version control workflows.
• Participate in team meetings and present progress and findings.
• Collaborate with internal and external partners professionally and effectively.
• Maintain awareness of cybersecurity and data privacy best practices.
• Prepare scientific presentations, posters, and visual materials.
• Assist with drafting and editing manuscripts, technical reports, and grant materials.
• Support machine learning model development and evaluation tasks.
• Perform other duties as assigned.
EDUCATION
- Required: Bachelor's Degree Basic Science.
- Preferred: Master's Degree Basic Science.
- Preferred: Medical Degree
WORK EXPERIENCE
- Required: 1 year Scientific or experimental research work experience. or
- Required: No experience required with preferred degree.
Preferred: Python coding 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.
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.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
