The successful candidate will work in close collaboration with academic and industrial partners, delving deep into the verification of Large Language Models (LLMs) based software programs. The focus of the position includes designing and implementing innovative verification methods to ensure the reliability and accuracy of LLM-based software programs, and actively engaging in the design and development of a system that generates high-quality data utilising LLMs. The project involves establishing methods to validate the efficacy of the prompting processes in getting accurate responses from LLMs and developing strategies to verify the overall reliability of the LLM-based software program. The postdoctoral researcher will further refine this approach, aiding in the development of a system optimised for high-quality data generation using LLMs. The successful candidate is expected to spend one or more internships in industry and liaise with industrial partners.

The University of Rochester’s Department of Computer Science seeks to hire an outstanding early-career candidate in the area of Artificial Intelligence. Specifically, we are looking to hire a tenure-track Assistant Professor in any of the following areas: Learning Theory, especially related to deep learning, Machine Learning Systems (ML Ops, memory efficient training techniques, distributed model training methods with GPUs/accelerators, etc.), or Deep reinforcement learning. We are especially interested in applications of these areas to large language models. Exceptional candidates at the associate or full professor level, or in other AI research areas such as foundational research in natural language processing (NLP), are also encouraged to apply. Candidates must have (or be about to receive) a doctorate in computer science or a related discipline.