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How to Apply

To be considered, a cover letter (1-2 pages) and full CV are required. The cover letter must be the leading page of your CV and should:

Specifically outline the reasons for your interest in the position andOutline your particular skills and experience that directly relate to this positionProvide a list of your 3 most significant publicationsProvide a list of at least three references and their contact informationA link to GitHub repos for relevant code (optional)

Starting salaries will vary depending upon the qualifications and experience of the selected candidate.

Job Summary

Weil Institute Postdoctoral Data Scientist Role Description

The Weil Institute is in search of a Postdoctoral Fellow to develop predictive analytics that will help improve the treatment of cardiac arrest patients in critical care areas such as intensive care units, emergency department and general hospital wards. We use rich, large datasets from a variety of sources including electronic health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors.

This position offers a unique opportunity to work closely with clinicians on applications of machine learning, signal processing and image processing in medicine with an extensive level of access to large clinical datasets. Research in the Weil Institute focuses on the development, validation and maintenance of clinical decision support systems and multimodal analytic platforms to translate advanced data science solutions into critical care.

The main focus of this position is on the analysis of the signals that are generated during cardiopulmonary resuscitation (CPR), including traditional patient monitors and a novel wearable sensor, to develop a tool to guide resuscitation strategies during cardiac arrest. As such, the ideal candidate should have experience in biomedical signal processing with prior publications on the subject.

This role requires active collaboration with our Data Science team as well as with other clinical collaborators within Michigan Medicine and in other institutions. The collaborations will include requirements gathering and regular interactions with other teams. Hence, strong communication skills are highly desired.

In addition to working on the development and validation of decision support systems, this role can evolve into leading data science projects and the design and development of new projects for other critical illnesses including trauma, neurologic emergencies, sepsis, acute respiratory distress syndrome and heart failure. This is a 2-year position with an option to extend based on performance evaluation and funding, reporting to the Weil Institute Director of Data Science and Project Principal Investigator.

Who We Are

The Max Harry Weil Institute for Critical Care Research and Innovation

The Weil Institute at the University of Michigan is one of the world's first comprehensive research enterprises devoted to transforming critical care medicine by accelerating science and moving it from bench to bedside. To do this, the Weil Institute brings together integrative teams of world-class U-M scientists, clinicians, and engineers with industry partners and funding sources to develop and deploy cutting-edge solutions that elevate the care, outcomes, and quality of life of critically ill and injured patients and their families.

Responsibilities*Develop and validate cutting edge machine learning and signal processing models to analyze waveforms generated by traditional patient monitors and a novel wearable sensor and build a decision support tool to guide CPRParticipate in the user interface and workflow development for the decision support toolIdentify data sets needed to properly develop and validate the CPR decision support toolParticipate in other projects involving the development of data analytics, including EHR, waveform and image-based and multi-modal applications, through consultation and collaboration with faculty, researchers, clinicians, and other team membersCommunicate clearly and consult with our multi-disciplinary team of scientists, developers, and clinicians.Write manuscripts to summarize the research findingsBe an expert on the latest machine learning techniques, methods, and research, especially deep learning literature, and how these methods apply to our use casesAbility to manage multiple projects and assignments with a high level of autonomy and accountability for resultsWrite technical patent applications explaining our unique innovations to a diverse audienceMentor students and junior team members while providing insight on the projects they are developingRequired Qualifications*PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related fieldFamiliarity with (biomedical) signal processingExperience working with clinical dataDeep learning expertise with advanced architectures including transformers, convolutional neural networks, and recurrent neural networks for multimodal (biomedical) dataDemonstrated experience with statistical analysis, time-series modeling, and handling of high-dimensional (biomedical) dataStrong data science and/or signal processing publication record5+ years of demonstrated technical knowledge of machine learning techniquesProficiency using data science tools (e.g., Python, R, MATLAB, MySQL, Jupyter Notebooks)Excellent verbal and written communication skills including the ability to communicate effectively and professionally with colleagues and stakeholdersAbility to understand and explain technical concepts to non-technical stakeholdersWillingness to learn and quickly adjust to new tools and systemsCapable of converting ambiguous problem statements into concrete project requirementsConfident teaching and coaching abilitiesDesired Qualifications*Familiarity with EHR data processing, data queries, and dashboardsFamiliarity with (biomedical) image processingFamiliarity with processing data collected using wearable devices (biomedical)Experience with natural language processing and Large Language Model (LLM)Strong biostatistics knowledge including survival analysis and causal inferenceExperience with reinforcement learning, agentic AI systems and autonomous decision-making frameworksData operations experience including data pipeline development, automated testing, continuous integration/deployment for ML models and data quality monitoringExperience with real-time ML models and deployment of AI modelsWork Locations

Our office is located on the University of Michigan campus in Ann Arbor, Michigan. This position is open to candidates who are seeking remote and/or hybrid location flexibility.

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

Background Screening

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Application Deadline

Job openings are posted for a minimum of seven calendar days.  The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.