Join the AIchemy team and become part of a world-class research and innovation community. We are building a dynamic group of innovators, researchers and professionals committed to advancing the integration of AI in both experimental and computational chemistry.
At AIchemy, we foster a collaborative and inclusive environment, embracing the power of diverse perspectives to drive ground-breaking research. We take pride in our commitment to inclusivity and in supporting the world-renowned reputations and facilities that make our work possible.
Explore our latest job opportunities below.
PhD – Putting a (Better) Brain in the Mobile Robotic Chemist
A funded studentship is available within the group of Professor Andy Cooper.
Based at the University of Liverpool, This studentship will focus on the development of “chemically-aware” agentic AI methodology that can orchestrate autonomous discovery, acting as the ‘brain’ for the robot chemist.
PhD – Discovering CO2-capture materials using robots and ‘Hive Mind’ hybrid intelligence in the Mobile Robotic Chemist
A funded studentship is available within the group of Professor Andy Cooper.
Based at the University of Liverpool, this studentship will aim to 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.
PhD – Experiment- and Human-Guided Representation Learning for Accelerated Chemical Discovery (Liverpool–Manchester)
Based at the University of Liverpool and University of Manchester, this PhD will develop fundamental AI methods that help chemists explore and navigate complex chemical spaces when data are scarce, high-dimensional, and continuously updated by new experiments.
PhD – From Single Robotic Chemist Action to End-to-End Experiment Resilience (Liverpool–Edinburgh)
Based at the University of Liverpool and University of Edinburgh, this PhD will develop fundamental robotic methods that would allow robotic chemists to reason through a series of learned skills and adapt the experimental workflow when experiments are interrupted due to adaptive chemical protocols, experimental and environmental changes and hardware failures.