-
of the e-Leaf into: A high-throughput multi-array platform for sensing in directed enzyme evolution in the context of a cascade – the multiplexed e-Leaf will be disruptive in this space, directly reporting
-
platforms, e.g. aerial drones, climbing robots, and remotely operated underwater vehicles, for capturing degradation data across turbine blades, towers, foundations, and subsea cables; (2) develop a machine
-
to the student’s interests through, e.g., 1) development of a more sophisticated gas sensing package or 2) situation-informed path-planning - considering reactive obstacle avoidance and ambient air flow. About the
-
-driven AI models that capture the underlying process–structure–property relationships governing metal additive manufacturing. By combining mechanistic modelling, in-situ sensing, and machine learning
-
the tight coupling between body dynamics, sensing, and interactions among neighbouring agents and their environments. The research will exploit an interdisciplinary approach that combines control theory
-
‑temperature operation. These features make HPCRs attractive for demanding applications including space power and exploration missions, remote/off‑grid energy supply, industrial heat, and resilient electricity grids. In