The threat of rising carbon dioxide (CO2) levels is well documented. Our goal is to create a delocalised global ‘Hive Mind’ that directs autonomous laboratory robots to discover engineered porous materials for atmospheric CO2 capture (a.k.a. DAC) using multiple data modalities. We will fuse human insight and AI agents with experimental and computational data streams in real-time, closed-loop robotic experiments to build a new paradigm for tackling complex societal challenges beyond DAC. In a strategic project co-funded by Google, we are proposing to fuse real-time experimental data from AI-powered laboratory robots with global, crowdsourced human expertise, AI agents, and computational predictions to create a unified, hybrid intelligence—a Hive Mind—powered by these four data modalities. We believe this will be necessary because of the exceptionally difficult scale-up challenges for DAC materials, which will defeat ‘brute force’ robotic strategies, human knowledge, AI agents, or large-scale computation used in isolation. It will also demonstrate a new approach to global cooperative research that is relevant to problems beyond DAC.
You will work in a unique interdisciplinary research environment since our team covers all the sub-areas required to tackle this challenge, including porous materials for CO2 capture (J. Am. Chem. Soc., 2025, 147, 23160), autonomous mobile robotic chemists (Nature, 2020, 583, 237; Nature, 2024, 635, 890), machine reasoning using LLMs (IJCAI, 2025, 4967), and ‘human-in-the-loop’ approaches (IJCAI, 2024, 3881).
The student will have the opportunity to develop expertise in experimental chemistry, automation and programming, as well as bridging them with AI into a fully-integrated autonomous discovery platform. The student will also be part of a larger team in Liverpool, connected to a large team of external researchers—the ‘Hive Mind’—who will inject their ideas and hypotheses into real-time experiments in our laboratories.
This project will be supervised by Prof Andrew Cooper FRS (Department of Chemistry), Dr Xenophon Evangelopoulos (Department of Chemistry), Dr Jeff Ayme (Department of Chemistry) and Dr Gabriella Pizzuto (Department of Computer Science and Informatics & Department of Chemistry). The supervisory team combines experts in porous materials for gas capture (Prof Cooper) with expertise in AI and computer science (Dr Evangelopoulos), chemical synthesis and automation (Dr Ayme), and robotics (Dr Pizzuto).
Essentially all the hardware tools required for this project have already been built within the group (synthesis robots, fast screening for CO2 sorption, etc.). The day-one challenge will be to integrate this into a viable real-time workflow that can then work in tandem with both machine reasoning (e.g., from LLMs) and a panel of human experts. This will require seamless teamwork as well as scientific, software, and engineering solutions.
This project is expected to start in October 2026 and is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry based in the Materials Innovation Factory at the University of Liverpool, the largest industry-academia colocation in UK physical science. The successful candidate will benefit from training in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. PhD training has been developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.