We are seeking a motivated postdoctoral researcher to work on a funded project at the UCSF Hypoxia Lab (hypoxialab.org) related to improving pulse oximeter performance in certain clinical scenarios including dark skin pigment and low perfusion states. Our lab has done seminal work to help identify limitations in current oximetry technology, and we are now embarking to solve these challenges. The Postdoctoral researcher will work closely with our multidisciplinary team to develop new validation protocols for use on human study subject testing, develop new in vitro testing devices to validate existing and new technologies, and collect data on performance of new and emerging clinical devices as part of the OpenOximetry.org project. This is a 1 year postdoctoral program, with possibility of extension for an additional year.
​Job Duties
- Design novel protocols and conduct experiments to study performance of clinical monitoring tools (with a focus on pulse oximetry). Perform statistical analysis, publish manuscripts on projects aligned with the primary research topic, present findings at national conferences and prepare grant applications to establish research independence.
- Lead the creation of two online, open access databases with oximeter performance data collected by our lab-based and in-hospital clinical studies; 1. The first database will contain raw performance data from our lab and collaborating labs, to help researchers and engineers identify root causes for oximeter performance problems; 2. The second database will contain oximeter performance summaries to help aid agencies, ministries of health and consumers better understand performance of oximeters. Postdoctoral researchers will lead not only in creation of these databases but also in designing data analysis plans which may include application of artificial intelligence (AI) models to predict device performance and data visualizationÂ
- For specific selected projects and analyses, the postdoctoral researcher will work in collaboration with the Pirracchio Data Science Lab. This UCSF-UCB lab has expertise in clinical artificial intelligence and specifically in modeling physiological signals and developing clinical decision support algorithms.
- Minimum qualifications: Postdoctoral program applicants must possess a doctoral degree (PhD, DrPH, or equivalent) in biomedical engineering or epidemiology/biostatistics or a related field. Strong data management, quantitative analytical and writing skills are required.
- Laboratory research experience and biomedical engineering or data science training is required
- Previous experience in medical device design, development, or regulatory frameworks is desired. Expertise in photonics/photometry is desirable.
- Experience in Stata, R, or SAS for quantitative analyses is required. Experience with Filemaker pro or related database management tools is required.
- Please send a CV, cover letter, one manuscript (published or unpublishsed), and the contact information for 2 references to [email protected]