Research Fellow - Data Science and Artificial Intelligence

Mayo Career Site US • Scottsdale, AZ

133d

About The Position

A postdoctoral research fellow position is available at the Cancer Data Science Lab (PI: Dr. Irbaz Riaz) at Mayo Clinic in Arizona. The research fellow will work in a multi-disciplinary team of clinicians, data scientists, and informaticians. Dr. Riaz is an Assistant professor in medicine and biomedical informatics. His lab is focused on developing artificial intelligence (AI) methods for electronic medical records data. The current projects heavily emphasize natural language processing (NLP), large language models (LLMs), multi-modal data integration, and computation oncology.

Requirements

• Demonstrated potential for research as evidenced by training and peer-reviewed publications.
• Proof of English proficiency is required for J-1 Short-Term Scholars, Research Scholars, Professors, Specialists, and Student Interns sponsored by Mayo Clinic.

Responsibilities

• Training and implementation of large language models that demonstrate good performance with healthcare data.
• Utilize artificial intelligence techniques, including natural language processing such as large language models, computer vision, and other deep learning methods, to build task-specific models for diverse applications in healthcare.
• Develop artificial intelligence frameworks for data extraction from free-text unstructured text reports and imaging/histopathological imaging data.
• Develop and/or improve predictive models using uni-modal and multimodal electronic health records system data (free text, imaging, genomics).
• Develop/enhance software for living clinical practice guidelines.
• Work with a multi-disciplinary team of physicians, computer scientists, and biomedical statisticians to improve artificial intelligence-based approaches for solving complex data science problems in cancer.
• Harbor excellent verbal- and written- communication and presentation skills.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees