What's Happening?
Indiana University Bloomington's Department of Mathematics, within the College of Arts and Sciences, is actively seeking applications for an open-rank faculty position in Mathematical Artificial Intelligence.
This initiative is part of the university's Faculty 100 program, with the ideal start date being August 1, 2027. The university is looking for an exceptional mathematician whose research significantly involves artificial intelligence, data science, or scientific machine learning. The successful candidate will hold a primary appointment in Mathematics and will have extensive opportunities for collaboration with faculty across various departments, including the Luddy School of Informatics, Computing, and Engineering, Data Science, Statistics, and the Institute for Scientific Computing and Applied Mathematics. Areas of particular interest include machine learning algorithms, formal proof assistants, and large language models. The role emphasizes connecting mathematical strengths with developing courses in topological data analysis, a new joint B.S. major with Luddy Data Science, undergraduate research, graduate training, and campus-wide AI and data science collaborations.
Why It's Important?
This faculty recruitment is crucial for Indiana University as it aims to strengthen its position in the rapidly evolving fields of artificial intelligence and data science. By integrating a mathematician with expertise in AI into its core mathematics department, the university is fostering interdisciplinary research and education, which is vital for addressing complex challenges in modern technology. This move will enhance the university's capacity to develop cutting-edge AI technologies and methodologies, contributing to advancements in areas like trustworthy AI, including stability, robustness, verification, interpretability, and generalization. The emphasis on both undergraduate and graduate training, along with curricular development in mathematical AI, signifies a commitment to preparing the next generation of AI professionals and researchers. This strategic investment in academic talent will likely attract more funding, partnerships, and top-tier students, solidifying Indiana University's role as a leader in AI research and education within the U.S.
What's Next?
Applications for the open-rank faculty position are currently being accepted, with full consideration given to those received by November 7, 2026. Following this deadline, a review of applications will commence immediately. The selected candidate is expected to establish and maintain an active, externally funded research program, engage in effective teaching and mentoring of both undergraduate and graduate students, and contribute to the development of the mathematical AI curriculum. They will also be instrumental in fostering collaborations between the mathematics department, the joint B.S. program with Luddy Data Science, and other AI- and data-intensive research initiatives across the campus. The university's commitment to an inclusive academic community means that candidates with demonstrated experience in supporting diversity will be highly valued. The appointment is for a 10-month period, ideally beginning in August 2027.
Beyond the Headlines
The establishment of this faculty position reflects a broader trend in higher education to bridge traditional academic disciplines with emerging technological fields. By embedding AI expertise within a mathematics department, Indiana University is acknowledging the fundamental role of rigorous mathematical foundations in the advancement of artificial intelligence. This approach moves beyond viewing AI merely as a computational tool and instead emphasizes its theoretical underpinnings, which are critical for developing more robust, reliable, and interpretable AI systems. The focus on areas like formal proof assistants and trustworthy AI highlights a growing recognition of the ethical and practical challenges associated with AI deployment. This interdisciplinary integration could lead to novel research breakthroughs and educational models that better prepare students for the complex demands of the AI-driven future, fostering a deeper understanding of AI's capabilities and limitations.
