Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; Newcastle University
- ; University of Birmingham
- ; University of Exeter
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; Swansea University
- ; University of Nottingham
- ; University of Southampton
- KINGS COLLEGE LONDON
- Newcastle University
- University of Cambridge
- University of Newcastle
- ; Aston University
- ; Cranfield University
- ; Lancaster University
- ; St George's, University of London
- ; The University of Edinburgh
- ; The University of Manchester
- ; University of East London
- ; University of Leeds
- ; University of Oxford
- ; University of Plymouth
- ; University of Strathclyde
- ; University of Surrey
- AALTO UNIVERSITY
- Abertay University
- Heriot Watt University
- Heriot-Watt University;
- UNIVERSITY OF EAST LONDON
- University of Cambridge;
- University of Exeter
- University of Hertfordshire
- University of Nottingham;
- University of Oxford
- University of Sheffield
- 28 more »
- « less
-
Field
-
digital construction technologies, including VR, IoT, machine learning, and physiological and behavioural data analytics. Experience with wearable sensors & physiological data (e.g., EEG, ECG, eye tracking
-
related discipline. You will have strong experience in one or more of the following areas: electrified powertrains, marine robotics systems, automation, or predictive maintenance using data analytics
-
to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
-
, deposition and characterisation tools, including bespoke burner-rig testing design for realistic thermal testing. Combination of experimental, analytical, and modelling training, ideal for interdisciplinary
-
emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision
-
will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
-
degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics
-
PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
at BHAFC and a supportive supervisory team with expertise in sleep, sports medicine, sports science, and data analytics. The PhD researcher will design, conduct, and analyse data and review literature
-
automatically assess solubility from arrays of micron-scale crystals deposited on a substrate. This project will give the student training in a wide range of skills applicable to modern analytical chemistry
-
(DT) communication protocols for interfacing with different types of systems and data sources. Using the DR research to create guidelines for the development of the ontological structure for the DT