Organisation Name: The University of Texas M. D. Anderson Cancer Center
Organisation Type:
City: Houston
State: TX
Country: United States
Job Description:
MISSION STATEMENT 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
The University of Texas MD Anderson Cancer and its Institute for Data Science in Oncology (IDSO) includes five major focus areas for the development and application of data science and emerging medical technologies for positive impact in clinical care and operations. Within the IDSO focus area on Quality, Safety, and Access is the Surgical Data Science Program under the direction of Dr. Jeffrey Siewerdsen. The Surgical Data Science Program includes a team of Computational Scientists working in areas of data science, systems engineering, and technology development. In collaboration with surgeons, physicists, and engineers, the Computational Scientist will contribute to research and translation of data science, multidimensional data analysis (including medical images), predictive modeling, and clinical outcomes.
The chosen applicant will have demonstrated experience with/in computing / programming (Python, Matlab, C++, CUDA, Julia, R and/or SQL), machine learning / deep learning methods including neural network design, computer vision / image analysis, and statistical analysis. Preference is for candidates with experience with common open source scientific computing/machine learning libraries including: scipy, pandas, statsmodel, OpenCV, XGBoost, PyTorch / TensorFlow. Experience with database languages such as SQL is also desirable. The candidate should also have experience with multiple modern techniques and algorithms in machine learning and statistical computing such as regression, clustering/segmentation, time-series analysis, recommender systems, predictive analytics, Bayesian modeling, data fusion, supervised/unsupervised learning, decision trees, A/B testing, natural language processing.
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
Planning and executing the details of experiments and in evaluating and interpreting the results.
Responsible for major participation in the development and revision of techniques, assembles and operates laboratory apparatus and equipment.
Collaborates or assists with supervisor and senior research staff with preparation of reports and grant requests.
Supervises technicians in their work and assists them as assigned or delegated.
Working with clinicians, clinical hardware and software (e.g., anesthesia, imaging, surgical robots, etc.), healthcare information systems (e.g., electronic medical records, EPIC, PACS, etc.) in the capture and curation of multidimensional data and development of new data science methods in surgery.
Development of computational modeling approaches related to surgical data science. Create data tools for analytics and data science team members.
Communicate with and provide consulting for internal teams and external collaborators on data models, analysis of findings, and process efficiency.
Create and maintain optimal data pipeline architecture. Build systems for optimal extraction, transformation, and loading (ETL) of data from a wide variety of clinical data sources. Build analytics tools that utilize the data pipeline to provide actionable insights into clinical workflow and/or operational efficiency.
