54 postdoc-in-postdoc-in-automation-and-control positions at University of Nottingham
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
control and proven planning, organisational and administration skills are essential for this role. Further details regarding the duties for the post can be found on the attached job role profile. What’s in
-
offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University
-
in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art
-
reliably (in terms of repeatability, yield etc) and controllably make metal organic frameworks at scales from g/hr to tn/hr. Motivation Promethean Particles is a spin out from the University and have
-
from the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art electric motor manufacturing
-
Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art electric motor manufacturing platforms at both locations
-
control of the electrical power system for aircraft applications, ensuring system stability across a wide range of nonlinear loads and operating conditions. Aim You will have the opportunity to research and
-
the volume and weight of power electronics converters. The research will take place at the Power Electronics, Machines and Control (PEMC) Research Institute, University of Nottingham. The successful
-
position that can be applied across a broad range of industrial sectors, bringing the benefits of passive linear optical superresolution to the domain of in-process control for additive manufacturing
-
in both technical and potentially non-technical skills of medical staff, such as poor team dynamics, problems with communication and a lack of leadership. This automated obtained data can then be fed