Physics Informed Neural Networks Jobs in Illinois

Description
Scope and Opportunity
The University of Chicago's Biological Sciences Division is searching for full-time scientists, physician-scientists, and engineers who bring innovative experimental, computational, and theoretical approaches to bear on fundamental questions in biology, medicine, and public health. This search is focused on realizing the power and promise of AI and statistical modeling approaches for biological sciences, capturing the full continuum from basic biological discovery to clinical translation and public health, including programs that bridge biophysics, computation, systems biology, bioengineering, and medicine.
We especially welcome applicants who develop innovative approaches to investigate biological complexity and emergent properties at any scale-from biomolecular design, molecular systems, and cellular physiology to cellular communities in tissues, organisms, and ecosystems. We welcome applicants who use quantitative and AI-driven methods to generate mechanistic insight, develop interpretable and predictive models, advance therapeutic and translational strategies for disease diagnosis, treatment, and management, or to develop new theory for biology.
Academic rank, track, tenure status, and compensation are dependent upon qualifications. Primary appointments will be in appropriate departments or units, most likely in the Biological Sciences Division (BSD), though potentially in the Physical Sciences Division (PSD) or Pritzker School of Molecular Engineering (PME), with possible secondary appointments in other relevant units depending on the candidates' research.
These positions are benefits eligible. The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Appointees will join a highly collaborative academic ecosystem in which outstanding basic science and clinical departments are co-located on a compact urban campus, with state-of-the-art core facilities, exceptional graduate and medical students, and opportunities to participate in multidisciplinary research, translation, commercialization, and entrepreneurship, including Hyde Park Labs, a new hybrid facility for academic research, science-based companies and the UChicago Science Incubator.
Research Priorities
The goal of this search is to recruit a cluster of faculty who will establish a distinctive community in AI-Enabled biology and medicine, forging new conceptual frameworks that predict, explain, and engineer biology across scales and with transformative consequences for both fundamental discoveries and applications to human health.
Areas of interest include, but are not limited to:

• Computational and experimental approaches that yield interpretable, mechanistic models of living systems, from molecules to cell signaling networks, to host-microbiome symbioses, organismal behavior and ecosystems
• Research aimed to discover the evolutionary origins of functional biological systems at any scale.
• Spatial and temporal biology through interpretable, multimodal representations of biological organization and dynamics across scales
• Digital twins - Generative, predictive representations of cells, networks, and tissues that forecast dynamics such as morphogenesis, tumor growth, neural computation, organismal behavior and cognition, immune-microbiome interactions, and regeneration
• Machine-learning foundations for multimodal integration of data across genomics, metagenomics, proteomics, metabolomics, imaging, clinical records, and other data modes
• Developing biologically inspired approaches for AI/ML
• Enabling measurement and instrumentation, including multiplexed and multispectral imaging and molecular profiling that resolve cellular features in tissues
• Experimental design and autonomous discovery to generate the information-rich datasets needed to build and test predictive models of biological function
• AI-enabled therapeutic development for human disease
• Computational pathology, radiology, and imaging, and clinically informed models of disease trajectory, patient stratification, and therapeutic response
• Trustworthy, interpretable, and equitable AI in biomedical research and medicine

Selection Process
The initial phase of the search is led by a committee composed of faculty from multiple departments and divisions rather than by a single hiring department. This phase is designed to identify leading candidates across the breadth of the search area and to consider how their scholarship could contribute to, and be advanced by, the University's scientific programs and intellectual environment. During an initial campus visit, candidates will meet faculty from multiple departments, institutes, and programs.
A follow-up visit will be organized by the departmental affiliation(s) best suited to support each candidate's work and long-term success. Additional information about the selection principles and the broader division-wide recruitment strategy is available here: BSD Faculty Recruitment.
A Division-Wide Recruitment Initiative
This search is one of five coordinated, open-rank searches through which the Biological Sciences Division and UChicago Medicine, in collaboration with the Physical Sciences Division and the Pritzker School of Molecular Engineering, are recruiting a cohort of exceptional faculty to expand the scale, disciplinary breadth, and human impact of biomedical research at UChicago. Candidates whose work spans more than one search area are encouraged to apply to multiple searches.

1. Cancer Biology and Immunology
2. Chemical Biology and Therapeutics
3. Translational Neuroscience
4. AI-Enabled Biology and Medicine (this ad)
5. Physician-Scientists-All Health-Related Areas

Application
Prior to the start of employment, qualifiedapplicants must have a doctoral degree or equivalent.
To be considered, those interested must apply through The University of Chicago, Academic Recruitment job board, which uses Interfolio to accept applications: https://apply.interfolio.com/190757.
Applicants must upload:

1. a cover letter
2. CV including bibliography
3. research statement
4. teaching statement
5. names and contact information for three references

Review of complete applications will start on September 30, 2026, and end when the positions are filled.
For instructions on the Interfolio application process, please visit http://tiny.cc/InterfolioHelp.