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Data Scientist - Digital Pathology
Join MD Anderson’s Translational Molecular Pathology team as a Data Scientist and help develop innovative AI technologies that have the potential to transform how cancer is understood, diagnosed, and treated. You’ll work at the intersection of artificial intelligence, multimodal pathology, molecular data, and oncology, developing computational methods that turn complex biological data into meaningful insights and move discoveries toward clinical translation.
What’s in it for you? This role offers the opportunity to work alongside a highly interdisciplinary team of scientists, pathologists, clinicians, and researchers on cutting-edge problems in cancer research. You’ll develop and evaluate state-of-the-art AI and machine learning approaches, build and maintain analytical pipelines and computational infrastructure, and contribute to the design of pathology, biological, and sequencing experiments that generate high-quality data for machine learning.
You’ll also have the opportunity to publish your work in high-impact journals and machine learning conferences, present findings at internal and external conferences, and collaborate with experts across disciplines to generate biologically meaningful results. As your expertise grows, you’ll also mentor junior trainees and help advance innovative computational approaches toward real-world clinical applications in oncology.
At MD Anderson, you’ll also enjoy a comprehensive benefits package, including competitive pay, an annual merit increase program, annual incentive opportunities, an employer-funded pension contribution, medical/dental/vision coverage, generous paid time off, and opportunities for professional growth and development.
If you’re a data scientist passionate about AI, machine learning, and cancer research—and want to see your work move beyond algorithms and toward meaningful clinical impact—this is an opportunity to make a difference at MD Anderson.
The ideal candidate will have digital pathology experience
JOB SPECIFIC COMPETENCIES
Develop impact-driven AI technologies for pathology Develop and maintain computational methods with AI in multimodal pathology.
Publish in high-impact journals and machine learning conferences.
Work with a highly interdisciplinary team to generate biologically meaningful results and work towards clinical translation of AI for oncology.
Keep current and evaluate state-of-the-art methods and tools, establish and help maintain computational infrastructure and analytic pipelines.
Participate in the design of pathology/biological/sequencing experiment to generate high quality data for machine learning.
Present results in collaboration meetings, internal and external conferences.
Mentor junior trainees with their projects.
Other
Other duties as assigned
Education
Required:
• Bachelor's Degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field
Preferred:
• Master's Degree in Science, Engineering or related field
• PhD in Science, Engineering or related field
Work Experience
Required:
• 3 years of scientific software or industry development/analysis experience OR
• 1 year of required experience with Master's degree OR
• With PhD, no experience required
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

