CORE COMPETENCIES:
The Department of Mathematics particularly encourages applicants with expertise in one or more of the following areas:
• Mathematical Foundations of AI and Machine Learning:
Optimization, statistical learning theory, inverse problems, uncertainty quantification, dynamical systems, or computational mathematics relevant to AI.
• AI and Data-Driven Modeling in Biomedicine:
Development of mathematical and computational methods for imaging, neuroscience, endocrinology, diabetes, or other data-intensive biomedical domains.
• Interdisciplinary Research and Collaboration:
Demonstrated ability to collaborate with clinicians, biologists, or engineers to develop mathematically grounded AI/ML approaches for complex biological and medical datasets.