Assistant Professor Tenure-Track Faculty Position in Optimization Machine Learning

The Ohio State University
Columbus, Ohio

College of Engineering:
Integrated Systems Engineering

The Integrated Systems Engineering (ISE) and Electrical and Computer Engineering (ECE; (Use the "Apply for this Job" box below). and  ) at The Ohio State University invite applications for an assistant professor tenure-track appointment in the area of Optimization for Machine Learning. The research area must complement the current research portfolio. This position will start as early as August 15, 2027. The candidate is expected to hold a 70% appointment in the ISE Department and 30% appointment in the ECE Department.
Immigration/visa sponsorship may be available in limited situations, but all decisions concerning immigration/visa sponsorship will depend on an evaluation of complexity and risk. We will not engage in immigration sponsorship for this position for individuals subject to the J-1 two-year home residency requirement or who will require consular processing for a visa to come to the United States to begin work at the university.

The successful candidate is expected to develop a rigorous research program in Optimization for Machine Learning (ML) and Artificial Intelligence (AI), with Operations Research (OR) providing foundational methods and tools. While all aspects of Optimization for ML/AI are considered, special areas of interest include foundational research in the following areas:

• Stochastic, zeroth-order, first-order, and adaptive methods for large-scale and nonconvex problems,
• Bilevel, multilevel, hierarchical, and sequential optimization as it relates to ML and AI,
• Integrated learning and optimization using stochastic, mixed-integer or other optimization methods,
• Distributed, federated, and communication-efficient optimization,
• Trustworthy, privacy-aware, and robust AI optimization.

The successful candidate is also expected to obtain funding, teach courses, and mentor students.

• Conduct high-quality high-impact research in the domain of Optimization for Machine Learning, Operations Research, Artificial Intelligence, and other areas of interest within ISE and ECE
• Publish the outcomes of the research in high-impact journals and conferences
• Demonstrate potential to secure funding to support research program
• Demonstrate potential to interact with other researchers, research institutes, and/or external partners to advance research
• Teach undergraduate and graduate courses within ISE and ECE
• Advise undergraduate and graduate students in ISE and ECE towards successful completion of their degree programs
• Support the department functions through departmental, college and university service
• An attitude conducive of good citizenship, including a commitment to interact with others in a professional, ethical, and constructive fashion

Ideal candidates will demonstrate significant AI expertise as a core element of their scholarship whether through the creation of new AI methods or novel use of AI techniques that materially advance knowledge, methods, or practice in their discipline.
For this search, “AI” is defined broadly but with a primary focus on optimization methodologies for AI/ML and AI-enabled decision-making. It includes (but is not limited to) Optimization for/with ML, Integrated Learning and Optimization, Reinforcement Learning, Deep Learning, Probabilistic Modeling, Trustworthy/Responsible AI (fairness, safety, privacy, robustness, interpretability), AI for Decision Making, Human-Centered AI, Natural Language Processing (NLP), Computer Vision, Control and Robotics, Scientific/Physics-Informed ML, AI Systems and Infrastructure, and Data-Driven AI advancements in and across disciplines.
In addition to the disciplinary requirements for potential selection as a faculty, a qualified candidate will develop, advance, or rigorously evaluate AI methods, lead AI-centered applications that produce generalizable methodological advances (e.g., new algorithms, models, evaluation frameworks,datasets/benchmarks, or system designs), design/adapt AI approaches to solve previously intractable questions in a domain leading to generalizable insights advancements.
Routine use of off-the-shelf AI tools that does not produce methodological innovation, or field-advancing knowledge is not sufficient for an AI faculty hire for this initiative.

• A Ph.D. in Industrial and Systems…