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Computational Scientist - Institute for Data Science in Oncology (IDSO)

University of Texas MD Anderson Cancer Center
Houston, Texas
Closing date
Jun 25, 2023

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Health Sciences
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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 University of Texas MD Anderson Cancer (MDACC) is recruiting Master's and PhD-level Computational Scientists for its newly established Computational Pathology program led by Professor Yinyin Yuan in the Department of Translational Molecular Pathology, which aims to develop cutting edge artificial intelligence (AI) and image processing methods for digital pathology. Working closely with the Institute for Data Science in Oncology (IDSO) and the Allison Institute, this highly collaborative program encompasses a large portfolio of innovative research using data and tissue samples collected in on-going translational studies and immuno-oncology clinical trials.

As the #1 cancer center in the U.S.A. and a leader in research and innovation, MDACC provides the ideal resources and environment for developing, testing, and deploying AI technologies for improved early cancer diagnosis and accurate treatment selection. The Computational Pathology program is a key focus area of the IDSO and addresses major priorities at the MD Anderson Cancer Center. The program enjoys strong institutional support and major computational resources from an institution with a track record for leading transformations in cancer care. The program is located in newly constructed translational research space in the heart of the Texas Medical Center at the MDACC main campus in Houston, Texas.

We seek Master's or PhD level computational scientists to develop, implement, and deploy innovative computational pipelines for digital pathology images. Successful candidates will develop computational methods using AI and deep learning, conduct data analysis and interpretation, seek opportunities for data integration with genomics and other healthcare data, collaborate with other data scientists, pathologists and clinicians, to together address key clinical challenges that will have an impact on our patients.

The ideal candidate will have strong computational and analytical skills particularly in deep learning, and is motivated by solving medical problems for patient benefits.


Develop computational methods by applying or designing deep learning methods and architectures for the datasets.

Keep current and evaluate state-of-the-art methods and tools, establish and help maintain computational infrastructure and analytic pipelines.

Evaluate image processing results and accuracy together with pathologists using quantitative performance metrics.

Participate in the design of pathology/biological/sequencing experiment to generate high quality data for machine learning.

Work with a highly interdisciplinary team to generate biologically meaningful results and work on clinical implementation.

Present results in collaboration meetings, internal and external conferences, if desired.

Prioritize and manage multiple projects in a timely and resource efficient manner.

Organize data and code, help write scientific publications, and publish code with documentation.


Develop impact-driven AI technologies for pathology.

Develop and maintain technologies for pathological image analysis using artificial intelligence. This includes the development or implementation of deep learning / machine learning / other statistical methods to help answer research questions and address unmet clinical needs. Participate in AI deployment evaluation and studies for the preparation of clinical implementations.

Assist collaborative research and scientific discoveries.

Work closely with other scientists in the team, pathologists, immunologists and clinicians. Be guided by curiosity. Identify creative and resourceful solutions for problems. Participate in collaborative meetings, present results and make ready results for publications of manuscript/abstracts.

Generate high quality data for scientific publications.

Produce output for scientific publications and co-author publications. Requires maintaining meticulous record of data processing and implementation. Use critical thinking and scientific rigor in data generation and interpretation.Discuss results with collaborators and help write the technology part of the manuscript for publication in peer reviewed scientific journals.

Other duties as assigned

Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Three years experience in scientific software development/analysis. With Master's degree, one years experience required. With PhD, no experience required. 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.


The University of Texas MD Anderson Cancer Center in Houston is one of the world's most respected centers focused on cancer patient care, research, education and prevention. It was named the nation's No. 1 hospital for cancer care in U.S. News & World Report's 2023 rankings. It is one of the nation's original three comprehensive cancer centers designated by the National Cancer Institute.

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