Senior Computational Scientist

Location
Houston, Texas
Salary
Competitive
Posted
June 04 2021
Ref
140650
Discipline
Health Sciences
Organization Type
Healthcare/Hospital
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.

SUMMARY

This individual will be responsible for designing and managing the process of building automated image interpretation tools and the extraction of tumor measurements to fulfil the TMI objective. The activity is an important sub-component of the overall TMI activity and requires a combination of computational skill, subject matter (imaging) expertise, technical expertise and organizational diligence/competency. The individual will be working with internal and external teams that are developing specific image analysis algorithms and will coordinate these developments in a fashion that supports scientific/technical evaluation and integration into the broader TMI effort.

Candidate must have in depth understanding of information systems with a specific focus on imaging principles and be able to communicate knowledge of same to co-workers effectively. Familiarity with DICOM standards, PACS integration, RIS, HL7 standards is highly preferred. Must be adaptable to change and able to interact with co-workers and customers in a positive manner, as well as communicate in an effective manner.

Additional Functions:
  • Participate and operate as the technical lead for the Institutional Tumor Measurement Initiative (TMI) Automation Team and coordinate with other strategic imaging research initiatives
  • Serve as a primary technical contact for members of the TMI automation team and collaborative faculty; manage and provide project and task updates, serve as technical and process subject matter expert
  • Demonstrate competency in the quantitative analysis of imaging data and work to develop deeper expertise on existing and emerging automated image analysis methods.
  • Keep current on relevant new technologies; understand and communicate their impact on both research and clinical practice; and provide input on their place in the overall institutional imaging research strategy.
  • Participate in the coordination of platform governance (e.g. roles, security, access) of relevant systems and work with Data Governance & Provenance Office to ensure alignment of procedures for both platform and imaging data governance
  • Liaise with the Enterprise Data Engineering and Analytics team and leadership to ensure efficient processes for cohort generation required for training, validation and interval quality assurance of TMI automation models/algorithms/tools
  • Participate in the institutional coordination of machine learning model management from development to clinical deployment, serving as the imaging technical subject matter expert
  • Liaise with IS Enterprise Development and Engineering technical teams to ensure supporting infrastructure and software needs are met and facilitate coordination between teams where there are common dependencies or overlapping technical concerns, to minimize duplication of effort.
  • Review business requirements, design, specifications and solutions in accordance with institutional standards and requirements.
  • Support the interaction with groups (internal and external; academic and commercial) that are developing TMI Automation technologies for potential integration with TMI.
  • Provide analysis of data, design and feasibility of proposed solutions
  • Lead, mentor and develop solutions in accordance with departmental and institutional standards and guidelines
  • Conduct review of teams' efforts to ensure consistent methodologies are followed and make recommendations where necessary
  • Coordinate activities between internal teams, customers and other departments

TMI Automation - Technical Lead

This individual will be responsible for designing and managing the process of building automated image interpretation tools and the extraction of tumor measurements to fulfil the TMI objective. The activity is an important sub-component of the overall TMI activity and requires a combination of technical expertise and organizational diligence/competency. The individual will be working with internal and external teams that are developing specific image analysis algorithms and will coordinate these developments in a fashion that supports evaluation and integration into the broader TMI effort.

Candidate must have in depth understanding of information systems with a specific focus on imaging principles and be able to communicate knowledge of same to co-workers effectively. Familiarity with DICOM standards, PACS integration, RIS, HL7 standards is highly preferred. Must be adaptable to change and able to interact with co-workers and customers in a positive manner, as well as communicate in an effective manner. Candidate will be encouraged to obtain CIIP (Certified Imaging Informatics Professional) certification within 12 months of hire.

Additional Functions:
  • Participate and operate as the technical lead for the Institutional Tumor Measurement Initiative (TMI) Automation Team and coordinate with other strategic imaging research initiatives
  • Serve as a primary technical contact for members of the TMI automation team and collaborative faculty; manage and provide project and task updates, serve as technical and process subject matter expert
  • Demonstrate competency in the quantitative analysis of imaging data and work to develop deeper expertise on existing and emerging automated image analysis methods.
  • Keep current on relevant new technologies; understand and communicate their impact on both research and clinical practice; and provide input on their place in the overall institutional imaging research strategy.
  • Participate in the coordination of platform governance (e.g. roles, security, access) of relevant systems and work with Data Governance & Provenance Office to ensure alignment of procedures for both platform and imaging data governance
  • Liaise with the Enterprise Data Engineering and Analytics team and leadership to ensure efficient processes for cohort generation required for training, validation and interval quality assurance of TMI automation models/algorithms/tools
  • Participate in the institutional coordination of machine learning model management from development to clinical deployment, serving as the imaging technical subject matter expert
  • Liaise with IS Enterprise Development and Engineering technical teams to ensure supporting infrastructure and software needs are met and facilitate coordination between teams where there are common dependencies or overlapping technical concerns, to minimize duplication of effort.
  • Review business requirements, design, specifications and solutions in accordance with institutional standards and requirements.
  • Support the interaction with groups (internal and external; academic and commercial) that are developing TMI Automation technologies for potential integration with TMI.
  • Provide analysis of data, design and feasibility of proposed solutions
  • Lead, mentor and develop solutions in accordance with departmental and institutional standards and guidelines
  • Conduct review of teams' efforts to ensure consistent methodologies are followed and make recommendations where necessary
  • Coordinate activities between internal teams, customers and other departments


Education
Required
: Bachelor's degree with a concentration in Science, Engineering or related field.

Preferred: Master's degree or PhD with a concentration in Science, Engineering or related field.

Experience
Required
: Nine years experience in scientific software programming with a concentration in scientific computing. With preferred degree seven years of experience required.

Preferred: PhD in bioengineering, computer science, physics, applied mathematics, computational neuroscience or related field. Experience in image processing (e.g. Custom routines, matlab, R, segmentation and quantitative image software packages). Experience in computer programming with proficiency in C/C++ or python

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

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