University of Texas Md Anderson Cancer Center

Automated, unbiased sample selection and scalable study design will immediately facilitate deep spatial investigations in landmark MD Anderson programs, including APOLLO and Patient MOSAIC, to direct novel data analysis, enable translational studies, and generate clinical impact.. Successful candidates will develop cutting edge artificial intelligence (AI) and image processing methods for digital pathology, conduct data analysis, collaborate and consult with pathologists and clinicians to address key clinical challenges that will have an impact on our patients.. Ideal candidates will have a minimum of a Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.. Develop and maintain computational methods using deep learning for pathological image processing.. 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.

machine learning

SUMMARY The University of Texas MD Anderson Cancer Center (MDACC) is the #1 cancer center in the U.S. and a leader in cancer research and innovation through our devotion to improving the care of cancer patients. This commitment is brought to life in the Institute for Data Science in Oncology (IDSO), a flagship program designed to reshape patient experiences and fast-track scientific breakthroughs via data-driven cancer care methodologies. The IDSO embodies a data-centric culture, pushing the envelope of modern care and venturing into uncharted territories of cancer research and treatment. It is home to a vibrant team of data scientists committed to unraveling complex cancer challenges, reducing time between diagnosis and treatment decisions, and accelerating drug discovery. MDACC is recruiting Data Scientists for its newly established Computational Pathology program. This program aims to distil meaningful insights from the extensive resources and data available at MD Anderson, particularly from cancer pathology that is currently benefiting from a digital revolution. Automated, unbiased sample selection and scalable study design will immediately facilitate deep spatial investigations in landmark MD Anderson programs, including APOLLO and Patient MOSAIC, to direct novel data analysis, enable translational studies, and generate clinical impact. MDACC provides the ideal 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 supports the IDSO's mission to drive high-impact discovery research by optimizing multidimensional data integration, analysis, and application. We seek data scientists to develop, implement, and deploy innovative computational pipelines for medical images. Successful candidates will develop cutting edge artificial intelligence (AI) and image processing methods for digital pathology, conduct data analysis, collaborate and consult with pathologists and clinicians to address key clinical challenges that will have an impact on our patients. Ideal candidates will have a minimum of a Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. With Three years of experience in scientific software development/analysis (specifically in Python, image processing and Deep Learning) CORE VALUES Caring: By our words and actions we demonstrate caring toward everyone.
We are sensitive to the concerns of our patients, their loved ones and our colleagues.
We are respectful and courteous to each other and practice cultural humility.
We promote and reward teamwork and inclusion. Integrity: We work together with professionalism to merit the trust of our colleagues and those we serve in all that we do.
We hold ourselves, and each other, accountable for our work - decisions and data - and for practicing our values and ethics.
We advocate for diversity and equity for our workforce, for those we serve and for our community.
We communicate frequently, honestly, openly and responsibly. Discovery: We embrace creativity and seek new knowledge from diverse perspectives.
We encourage continuous learning, seeking out information and new ideas.
We team with each other to identify and resolve problems.
We seek personal growth and enable others to do so. Safety: We provide a safe environment - physically and psychologically - for our patients, for our colleagues and for our community.
We create a sense of security and empowerment and are committed to keeping one another free from harm.
We embrace a framework and best practices for the highest quality of care and service.
We inspire trust by modeling excellence in our work and acceptance of each person's contributions. Stewardship: We protect and preserve our institutional reputation and the precious resources - people, time, financial and environmental - entrusted to us.
We prioritize the health and well-being of each other.
We act responsibly to safeguard the institution's finances.
We ensure the proper care and use of time, data, materials, equipment and property afforded to us. JOB SPECIFIC COMPETENCIES Develop impact-driven AI technologies for pathology Develop and maintain computational methods using deep learning for pathological image processing. Work with a high interdisciplinary team to generate biologically meaningful results and work towards clinical implementation of AI technology for oncology. Develop key performance metrics to demonstrate image processing accuracy. 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. Prioritize and manage multiple projects in a timely and resource efficient manner. Organize and provide up-to-date documentation for data and code, and help write scientific publications and reports. Other Other duties as assigned REQUIREMENTS 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. Education Preferred: Master's or Ph.D. Experience Required: Three years experience in scientific software development/analysis Experience Preferred: With Master's degree, one years experience required. With Ph.D., 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. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html Additional Information
Requisition ID: 160749
Employment Status: Full-Time
Employee Status: Regular
Work Week: Days
Minimum Salary: US Dollar (USD) 84,500
Midpoint Salary: US Dollar (USD) 105,500
Maximum Salary : US Dollar (USD) 126,500
FLSA: exempt and not eligible for overtime pay
Fund Type: Soft
Work Location: Hybrid Onsite/Remote
Pivotal Position: Yes
Referral Bonus Available?: No
Relocation Assistance Available?: Yes
Science Jobs: No #LI-Hybrid
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