A cover letter is required for consideration for this position and should be attached as the first page of your resume. In your cover letter, please address how you meet the required qualifications and your interest in RL data analysis, programming and data capture. Those who do not meet the minimum requirements or submit a cover letter will not be considered.
The Michigan Neuroscience Institute (MNI) is a cross-campus research community founded in 1955 that unites more than 170 faculty to advance discovery across molecular, cellular, systems, and computational neuroscience. This environment provides exceptional opportunities for interdisciplinary collaboration, access to cutting-edge cores, and engagement with a vibrant neuroscience community.
Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components: patient care, education and research that together enhance our contribution to society.
The Comprehensive Mobile Precision Approach for Scalable Solutions in Mental Health Treatment (COMPASS) project is looking for an Application System Analyst/Programmer Intermediate for our new NIMH project. COMPASS is focused on the effects of machine learning, wearable and mobile technology to both reduce mental health symptoms and predict response to clinic-based treatments. The ideal candidate should be passionate about building data and software infrastructure to power precision mental health research that integrates mobile sensing, electronic health records, and reinforcement learning. We are looking for someone with a demonstrated background in programming who is detail-oriented and will work to conceptualize, develop and implement complex program designs to assist with the reinforcement learning AI agent to coalesce complex data from multiple sources (wearable devices, smartphones, survey answers).
Responsibilities include, but are not limited to:
Reinforcement Learning Algorithm Development and Implementation (35%)
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Lead the design, implementation, and operation of reinforcement learning algorithms.
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Contribute to study design discussions, translate research questions into technical requirements, and communicate options, tradeoffs, and timelines to stakeholders.
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Uphold data governance and research compliance, including HIPAA and data use agreements, and support secure data sharing with partner institutions.
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Track emerging methods and tools in the reinforcement learning field and evaluate and deploy those that improve performance, cost, or scientific value.
Use Large Language Models to Generate Intervention Messages (25%)
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Lead the development of a sustainable infrastructure for generating intervention messages to deploy to study participants on a large scale across multiple projects.
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Design an interface for collecting and integrating study team feedback in the message creation process.
Code and documentation development (15%)
Data Team work (15%)
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Participate as a team member in weekly discussions on analysis and improvement of data collection, quality of data analyses, programming and documentation.
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Communicate proactively with project managers and PIs about data progress, timelines, and issues.
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Identify and resolve time-sensitive data issues.
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Document reinforcement learning process.
Manuscript Development (10%)
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Develop data visualizations to effectively communicate data in reports, flowcharts, and dashboards.
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Support the writing team by preparing figures, methods, and reproducible analyses; coauthor manuscripts and lead selected method or application papers, including drafting, submission, and revisions.
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Support research design, determining and interpreting research results, and independently writing up results of analyses.
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Master's degree in Biostatistics
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Demonstrated background in reinforcement learning with proven experience in building adaptive, sequential decision systems for health research.
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Reinforcement learning-based contextual bandits in applied settings.
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Integrating wearable, smartphone, survey, and longitudinal behavioral data.
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Designing algorithms and workflows to implement existing theoretical literature within an online, clinical setting.
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GPU-based statistical computations.
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Local LLM data pipelines.
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Proficiency using relevant tools, including Python, R, Git, and version-controlled scientific workflows.
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Background in database design and server-based computing.
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Clear, professional communication skills, with the ability to translate between technical and scientific audiences; demonstrated record of collaboration and independent problem solving.
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Willingness to learn and quickly adjust to new tools and systems.
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Ability to manage multiple projects and assignments with a high level of autonomy and accountability for results.
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Experience in mentoring and supervising the work of a team, peers, and staff.
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Capable of converting ambiguous problem statements into concrete project requirements.
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Ability to understand and explain technical concepts to non-technical stakeholders.
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Experience with cloud platforms (for example, GCP or AWS).
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Familiar with Michigan Medicine data requirements and procedures, including EPIC Electronic Health Records.
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Experience working with big data.
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Experience working with PHI.
Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world?s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.
What Benefits can you Look Forward to?
- Excellent medical, dental and vision coverage effective on your very first day
- 2:1 Match on retirement savings
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.
Our office is located at the University of Michigan's North Campus Research Complex. This is a hybrid work environment.
This position is term-limited for 2 years (ending May 2028) with the possibility of renewal based on need and available funding. At the end of the stated term, your appointment will terminate and will not be eligible for Reduction-in-Force (RIF) benefits. This term-limited appointment does not create a contract or guarantee of employment for any period of time as you will remain subject to disciplinary or other performance measures, up to and including termination, at the will of the University in accordance with existing University policy and standards for employee performance and conduct.
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.
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 any time after the minimum posting period has ended.
The University of Michigan is an equal employment opportunity employer.
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