Topic: AI for science

Under the theme Aspiration, Action, Anticipation: AI for Science Looking to 2030, this summit asks how AI is already changing scientific practice and how research may develop over the next few years. Researchers will examine scientific reasoning and discovery alongside applications in cancer biology, climate and weather prediction, animal behaviour and cosmology. Talks, discussion and a poster session connect methodological advances with practical scientific problems. Confirmed contributors include Max Welling, Hana Aliee, Boris Bolliet, Cait Newport, Richard Turner, Neil Lawrence, Stephen Rob

Exploratory projects pair AI expertise with a domain researcher to address a specific challenge in engineering biology, advanced materials, quantum technologies, medical research or fusion energy. Outputs may include prototypes, feasibility evidence, collaborations or research roadmaps; AI-method development without domain benefit is outside scope. Projects last up to 12 months and start on 26 April 2027. Applications opened 29 September 2026 and close 1 December 2026 at 16:00 UK time. Funding remains subject to Full Business Case approval.

Build experimental biology programmes that help AI systems perform useful scientific research. Design molecular biology and biochemistry experiments, develop functional high-throughput screens and collaborate with computational researchers on AI-agent planning and evaluation. The role connects laboratory evidence with model capabilities. The advertised annual salary is USD 300,000–320,000. Anthropic’s hybrid policy requires at least 25% office attendance, with some roles requiring more; applications are currently open.

Develop computational biology research that advances the scientific usefulness of AI systems. Work may span large-scale sequence analysis, structural biology, phylogenomics and screening datasets, with analysis pipelines that inform experimental hypotheses and AI-agent evaluation. The advertised annual salary is USD 300,000–320,000. Anthropic’s hybrid policy requires at least 25% office attendance, with role-specific requirements potentially higher. The vacancy currently accepts applications.

Paco Villaescusa surveys the growing role of numerical simulations and AI in cosmology. Quijote and Backlight explore how much information about the Universe can be recovered beyond conventional summary statistics, including nonlinear structure and higher-order relationships. CAMELS addresses uncertainty in galaxy formation and other astrophysical processes, while DREAMS examines dark-matter predictions in the presence of baryonic effects. The seminar then considers automated research workflows through Denario, a system that develops hypotheses, plans analyses, writes and executes code, and i

ISTA Lecture by Klaus Robert Müller (TU Berlin & Korea University, Seoul) on how machine learning and AI enable scientific research, particularly in medicine and chemistry, and on explainability techniques for extracting understanding from machine learning models.

RIKEN invites junior researchers with advanced mathematical, computational or information-technology skills to support research across its host laboratories, including AI for Science. Around five appointments are planned. Fellows primarily join the Research Engineer Enablement Office in Wako and also work with a host laboratory; annual contracts may be renewed for a maximum of three years. Applicants must first secure a prospective host’s agreement. Mandatory registration closes on 23 October 2026 at 17:00 JST; documents and two reference letters are due on 30 October at 14:00 JST. The listed

Collaborate with interdisciplinary teams to develop infrastructure for materials science experiments and apply AI/machine learning to accelerate discovery of new functional materials through computational simulation and automated experimentation.