Job details
Facility undisclosed
Ave South Birmingham, AL
The University of Alabama at Birmingham Portal | Heersink School of Medicine - Assistant Professor (Data Science) - Anesthesiology Skip to Main Content (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-P7PM9Z7'); .header-inner { min-height: 0px; max-height: 100px; } Toggle navigation Home Search Jobs Log In /Create Account Help FAQs .navBG ul#navLinks > li > a, .navBG ul#customnav > li > a { background-color: #FAFDF5; color: #1E6B52; } UAB Home UAB Human Resources Benefits About Birmingham Heersink School of Medicine - Assistant Professor (Data Science) - Anesthesiology Bookmark this Requisition Print Preview | Apply for this Job Posting Details Position Information School/College School of Medicine Title Heersink School of Medicine - Assistant Professor (Data Science) - Anesthesiology Assignment Category Full-Time Rank Assistant Professor Tenure Status Non-Tenure Track Payroll Status Faculty 12 Job Description We are seeking a highly motivated and skilled Assistant Professor of Data Science to join the Department of Anesthesiology and Perioperative Medicine. The successful candidate will begin by providing insights and recommendations through advanced data analysis, contributing to various data science projects. Over time, the role will transition to leading a waveform lab, focusing on innovative research and development in healthcare data science. This transition will involve creating a team of PhD students, Post-Doctoral Fellows, and junior faculty. Initial Responsibilities: Data Analysis and Hypothesis Testing: Utilize advanced mathematical, statistical, scientific, and computational techniques to develop, test, and validate hypotheses. Techniques may include probability models, artificial intelligence (AI), machine learning, data mining, pattern recognition, data visualization, predictive analytics, data warehousing, artificial intelligence, and other complex methods. Tool and Model Development: Develop new tools and models or integrate existing ones to analyze large and unstructured data sources, particularly with generative AI. Presentation of Findings: Prepare and present interpretations of data findings to internal and external clients. Mentorship: Mentor and train junior staff, faculty, and trainees, fostering a collaborative and educational environment. Collaboration: Work with university-wide resources (e.g., graduate CS department, informatics group, medical faculty and staff, epidemiologists, statisticians) to maximize data usage for improving patient outcomes. Knowledge Sharing: Demystify complex deep learning and statistical learning techniques, both in application to our data and in understanding published research. Project Support: Strengthen ongoing projects such as designing patient risk scorecards, waveform analysis, and generative AI integration. Transitioning Responsibilities: Waveform Lab Leadership: Lead the establishment and development of a waveform lab within the data science team. Hiring and Training: Recruit, hire, and train PhD students, Post-Docs, and junior faculty, providing guidance and leadership in their research endeavors. Research Direction: Set the research agenda for the waveform lab, focusing on innovative applications of data science in anesthesiology. Funding and Grants: Secure funding through grants and other sources to support the lab’s research activities. Collaboration Expansion: Expand collaborative efforts with other departments and institutions to enhance research output and impact. Academic Contributions: Contribute to the academic mission of the department through teaching, publishing research, and participating in academic conferences. Required Qualifications PhD in Mathematics, Science, Data Science, Computer Science, Statistics, or a related field. Strong background in advanced data analysis techniques, including artificial intelligence, machine learning, data mining, and predictive analytics. Experience with large, unstructured data sources and the development of analytical tools and models. Proven track record of research and publication in relevant fields. Excellent communication skills, with the ability to present complex findings to diverse audiences. Experience in mentoring and tr
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UAB Heersink School of Medicine