-
research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
-
The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
-
Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
-
the Clean Energy Processes (CEP) Laboratory . The CEP team conducts research on fundamental aspects of thermodynamics, fluid flow, heat and mass transfer processes with applications to the development
-
such as stakeholder preferences and supply chain issues. The successful applicant will join the research group of Dr Elina Spyrou, which currently has three PhD students and a postdoctoral researcher. The
-
, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods. It is also essential that you are highly experienced in setting up continuous
-
development and refinement accordingly. We are looking for a highly organised, driven, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods
-
your PhD journey in the heart of London at the newly established City St George's, University of London, a dynamic institution formed from the merger of City, University of London and St George's
-
model predictive control (MPC) methods to enable large groups of buildings to dynamically form coalitions and provide flexible energy services. Your work will incorporate advanced robust MPC techniques
-
treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews