Computational & Data Science Research Specialist 2 - 138357

The Department of Radiation Medicine & Applied Sciences (RMAS) has a strong commitment to research in a wide variety of disciplines including imaging, medical physics, health outcomes and equity, basic science and radiobiology, technology development and implementation, clinical trials, education, and systems engineering and design. RMAS researchers are funded by multiple societies and organizations including the National Institutes of Health (NIH), National Cancer Institute (NCI), Department of Defense (DOD), American Society of Radiation Oncology (ASTRO), and the Radiological Society of North America (RSNA).

This position supports research activities in the Physics Division of the Department of Radiation Medicine and Applied Sciences, with a primary focus on the development of AI- and machine learning-based tools for clinical applications. The Computational and Data Science Research Specialist will participate and collaborate closely with physics faculty on funded and exploratory research projects aimed at advancing radiation therapy through data-driven and computational methods. This work will help guide the adoption of emerging computational and AI technologies in support of clinically motivated medical research.

The individual will use principles from computational science, computer science, and data science to design, develop, and evaluate research software and analytical pipelines. Core responsibilities include building, training, and validating machine learning and deep learning models; working closely with physics team in planning and developing algorithms for data processing and analysis; and leveraging high-performance and supercomputing resources to support large-scale research workflows.

The Research Specialist will exercise judgement to optimize and maintain a range of computational, data science, and cyberinfrastructure tools. The role involves technical contributions to projects of moderate scope, including evaluating emerging AI, data, and HPC technologies and assessing their applicability to ongoing and future research initiatives.

• Six years of related experience, education/training, OR a Bachelor's degree in related area plus two years of related experience/training.

• Working knowledge of HPC / Data Science / CI.

• Working knowledge of applications programming and web development, databases and data systems, statistical methods and tools, and modern biology and applicable field of research.

• Demonstrated working knowledge of one of the following: Scalable systems, distributed systems, or systems performance. Demonstrated working knowledge of resolving broad computing / data / CI problems using introductory and / or intermediate principles.

• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences. Demonstrated effective communication and interpersonal skills.

• Ability to manage multiple assignments through prioritizing tasks and managing time.

• Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines.

• Interpersonal skills in order to work with both technical and non-technical personnel at various levels in the organization, and to iteratively improve data science methodologies working with biomedical domain experts.

• Working project management skills.

• Working knowledge working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base.

• Intermediate knowledge of artificial intelligence theory, specifically machine and deep learning models

• Master's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization.

• Demonstrated ability to contribute research and technical content for grant proposals.

• Domain knowledge in radiation therapy or medical imaging.

• Employment is subject to a criminal background check.

• Exercise the utmost discretion in managing sensitive information learned in the course of performing their duties. Sensitive information includes but is not limited to employee and student records, health and patient records, financial data, strategic plans, proprietary information, and any other sensitive or non-public information learned during the course and scope of employment. Understands that sensitive information should be shared on a limited basis and actively takes steps to limit access to sensitive information to individuals who have legitimate business need to know. Ensure that sensitive information is properly safeguarded. Follow all organizational policies and laws on data protection and privacy. This includes secure handling of physical and digital records and proper usage of IT systems to prevent data leaks. The unauthorized or improper disclosure of confidential work-related information obtained from any source on any work-related matter is a violation of these expectations.