Assistant Professor of Computer Sciences: RISE-THRIVE

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Job Category:

Faculty

Employment Type:

Regular

Job Profile:

Assistant Professor

Job Summary:

The Department of Computer Sciences at the University of Wisconsin-Madison has embarked on a multi-year effort to grow its faculty, enhance its strengths in many areas of computing, and extend its impact in interdisciplinary areas. As part of this endeavor, and as part of the department's involvement in the Wisconsin Research, Innovation and Scholarly Excellence-Transforming Healthspan through Research, Inno Vation, and Education (RISE-THRIVE) initiative, which focuses on advancing the "human health span" (the number of years a person is living with good health and well-being), we invite highly qualified candidates with a background in at least one of computational optimization and modeling, embedded sensing systems, and human-centered technologies and expertise in applying methods and principles from these areas to problems related to human health and wellbeing to apply to the position at the assistant, associate, or full professor levels that will begin in August 2026.

Successful candidates will work in a highly interdisciplinary environment and collaborate closely with the Department of Communication Sciences and Disorders, La Follette School of Public Affairs, the Center for Healthy Minds, School of Nursing, School of Medicine and Public Health, and other units on campus.

Duties will include scholarly research in application of optimization, machine learning, and human-centered AI to human health and wellbeing and related areas of computer science; individual and classroom teaching in computer science at the undergraduate and graduate levels and advising and mentoring graduate students majoring in computer science or related areas; service to the department, college, university, and academic community, nationally or internationally.

The successful candidate will participate in interdisciplinary and collaborative efforts with other departments, schools and colleges.

The successful candidate, as a member of the College of L&S will proactively contribute to, support, and advance the college's commitment to excellence among all aspects of their teaching, mentoring, research, and service.

We seek candidates whose primary expertise lies in computer science, particularly in areas including machine learning, optimization, natural language processing, sensing systems, embedded wearable and IoT systems, computer vision, human-computer interaction, or robotics, and who apply these methods to advance human health and wellbeing. Candidates should demonstrate methodological depth in one or more of these areas and an ability to collaborate effectively across disciplines to address challenges in health and healthcare delivery.

Applicants' research will generally fall into one of the following illustrative profiles:

1. Computational health optimization and modeling

Applicants conducting research at the intersection of optimization, machine learning, and artificial intelligence motivated by the need to advance the understanding and improvement of human health and wellbeing. Areas of interest include data-driven modeling of phenotypes and endotypes of health risk; explanatory and predictive modeling of health outcomes; and development of algorithmic approaches that can be deployed to optimize health services and interventions.

As an example:
We would welcome work that incorporates behavioral predictors of health, including mental health, addiction, and loneliness, into computational approaches to inform precision health strategies.

2. Human-centered health AI

Applicants conducting research in the development and application of human-centered artificial intelligence, interactive systems, and explainable machine learning to improve health and healthcare delivery. Areas of interest include AI-enhanced support for clinical processes (e.g., electronic health records, provider-patient interactions), multimodal sensing of behavioral health markers, and intelligent systems that assist in the management of chronic and neurodegenerative conditions. We especially encourage work that bridges machine learning, behavioral science, and healthcare systems to create usable, explainable, and effective AI-driven interventions.

3. Intelligent and embedded health sensing systems

Applicants conducting research in the development and application of embedded and AI-driven computing systems for health monitoring and intervention. Areas of interest include wireless and multimodal in vivo sensing of physiological and behavioral markers, low-power edge intelligence for continuous health monitoring, and adaptive systems that integrate sensing, communication, and machine learning to support clinical and personal health applications. We especially encourage work that is holistic in nature and bridges embedded systems,…