-
, economic viability, and robustness to realistic operational uncertainty. PhD (or equivalent) in control engineering or closely related discipline. Track record in at least two areas: model predictive control
-
) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
-
) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
-
deep learning methods to enhance the predictions beyond existing data. By incorporating microstructural features into predictive models, the aim is to create a reliable data-driven modelling framework
-
academic background, successful candidates should have experience in one or more of the following: Experience of data-driven modelling and optimization-based analysis. Knowledge of fluid mechanics. Knowledge
-
: Experience of data-driven modelling and optimization-based analysis. Knowledge of fluid mechanics. Knowledge of control theory and optimization. Knowledge of partial differential equations. Have a strong
-
. The School of Architecture, Computing and Engineering (ACE) at the University of East London (UEL) is deeply embedded in London’s dynamic and diverse communities. Known for its innovative, impact-driven