Generative AI

…methods, machine learning and generative AI, expected to begin in July 2027. Research may address molecular and materials discovery, electronic structure, simulation, sustainability or AI-enabled experimentation. The appointment is shared with EECS or IDSS, and includes research leadership, mentoring and teaching in both academic communities. Application consideration begins on 15 November 2026.

Develop and use computational, machine-learning or generative AI methods to investigate fundamental molecular, cellular or organismal mechanisms. The faculty member holds a shared appointment in Biology and the Schwarzman College of Computing, builds an independent programme, teaches computational approaches to biology and mentors students. Computational and experimental laboratory space may be provided according to research needs.

Postdoctoral research advancing generative AI applied to biology, including developing frontier biological foundation models; requires a PhD in computer science or related fields and expertise in Python and deep learning frameworks.

Dan Meyer considers the questions generative AI raises for mathematics learning after four years of rapid technological development. He argues that its novelty has been accompanied by educational adoption and institutional change falling short of early expectations, including lower-than-anticipated teacher use. The session explores what the technology can do, what students need and what teaching entails, using these questions to examine AI’s contribution to education.

Generative AI is changing scholarly publishing. Editors of applied linguistics journals discuss its effects on publication practices and the challenges and opportunities facing their field. The facilitated panel brings together perspectives from RELC Journal, Applied Corpus Linguistics, and English for Specific Purposes to consider how scholarly publishing can respond to these changes.

Vincent Racaniello, Kathy Spindler and Brianne Barker discuss research using generative AI to design complete bacteriophage genomes, including reported viable phages active against antibiotic-resistant bacteria. They also examine a study linking recombinant shingles vaccination with lower cardiovascular-event risk. The discussion connects genome modelling, experimental virology and vaccine research, alongside listener letters and weekly selections.

David Shih surveys generative AI applications to discovery in fundamental physics. Normalising-flow methods enable model-agnostic anomaly searches at the LHC and identification of stellar streams and faint galaxies in astronomical data. Generative inference also supports pulsar-timing gravitational-wave analysis and, combined with physics-informed networks, measurements of local dark-matter density. The talk concludes with agentic language models and new forms of collaboration between researchers and AI.

Generative AI is fundamentally transforming the software development industry by improving processes such as software testing, bug detection, bug fixes, and developer productivity. This talk explores how AI-driven techniques, particularly large language models (LLMs), are being utilized to generate realistic test scenarios, automate bug detection and repair, and streamline development workflows. As these technologies evolve, they promise to improve software quality and efficiency significantly. The discussion will cover key methodologies, challenges, and the future impact of generative AI on t