Mayo Postdoctoral position in Information & Decision Engineering
This announcement is seeking applicants for a postdoctoral position to study diagnostic decision-making in emergency and acute care using augmented human intelligence.
Drs. Kal Pasupathy and Mustafa Sir in partnership with emergency medicine physicians at the University of Michigan and Mayo Clinic were recently awarded a 4-year $2.5M research grant from AHRQ for a Patient Safety Learning Laboratory to improve diagnosis in emergency and acute care settings. Diagnostic decision-making is a highly complex cognitive process involving uncertainty, making it susceptible to errors. Clinicians working in emergency departments (EDs) are particularly vulnerable to making diagnostic errors due to time-pressured decision-making in a hectic environment. This team science award will study patient, provider/care-team and system level factors in emergency/acute care, and use a combination of human and machine intelligence to improve diagnostic accuracy and safety. The grant is for development of diagnostic triggers and implementation and dissemination/scale of the Learning Laboratory concept through two academic and two community-based EDs. This award builds on years of discovery/innovation work in Clinical Engineering Learning Laboratories (CELLs). Mayo Clinic's Kern Center for the Science of Health Care Delivery had launched and funded ED CELL in 2014, which was followed by Radiology CELL, funded by the clinical practice in 2016. The recently funded lab is the third in such series.
Mayo Clinic is the first and the largest integrated medical group practice in the world and has been consistently ranked at the top for patient care and research. The Kern Center is a hybrid center reporting to the Deans of Research and Practice with a mission to advance science and transform care delivery. The Information & Decision Engineering (IDE) program brings together data and decision scientists along with clinical experts and practitioners in a long-term collaborative environment. The program hosts faculty members, postdocs, analysts and students as summer interns. The individual will join a growing postdoctoral program, have an academic appointment in the Department of Health Sciences Research and will be co-mentored by Drs. Pasupathy and Sir and emergency physicians. S/he will have the opportunity to advance decision science methodology with strong clinical relevance, translate innovation to improve the diagnostic process and engage with a broad range of professionals, through the Learning Laboratory. Past projects in the program can be categorized as: operational decision making to impact patient experience and clinical decision making for personalized medicine and population health. The growing postdoctoral program has past postdocs joining academic/research institutions as faculty/research scientists.
The ideal candidate will have expertise in big data/modeling and strong interest in healthcare. Specific methodological areas of interest includes machine learning, natural language processing and deep learning, with an understanding of traditional systems engineering methods. Healthcare experience, though not required, is a plus. Previous experience with large datasets is preferred. These are two-year positions, renewable after one year based on performance. Performance expectations for a postdoc include understanding clinical relevance, contributing to science and methodology, leading scholarly publications, participating to seek external funding and participation in translation to practice. Candidates with a PhD (or near completion) are encouraged to apply.
Please submit CV with references to Dr. Kal Pasupathy (pasupathyk@mayo.edu). Shortlisted candidates will have brief interviews with faculty at INFORMS in Phoenix. Additional documents will be requested for subsequent round of the interview process.