Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Sheffield
- University of Nottingham
- ; Swansea University
- ; The University of Edinburgh
- ; The University of Manchester
- AALTO UNIVERSITY
- University of Bristol
- University of Newcastle
- ;
- ; City St George’s, University of London
- ; University of Birmingham
- ; University of Bristol
- ; University of Exeter
- ; University of Oxford
- ; University of Sheffield
- KINGS COLLEGE LONDON
- The University of Manchester
- UCL
- University of Cambridge
- ; Aston University
- ; Coventry University Group
- ; Cranfield University
- ; Loughborough University
- ; University of Cambridge
- ; University of East Anglia
- ; University of Nottingham
- ; University of Southampton
- ; University of Surrey
- ; University of Warwick
- Harper Adams University
- Newcastle University
- The University of Edinburgh
- University of Birmingham
- University of Glasgow
- University of London
- University of Nottingham;
- University of Warwick
- 28 more »
- « less
-
Field
-
performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
-
of the assembly of these complex microbial communities using ecological theory and mathematical models. The questions we address are: (1) how does the microbial community change during cultivation
-
correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
-
the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
-
noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a
-
successful courses or projects) Be proficient in programming (preferably in Python ot Matlab). Ideally familiar with machine/deep learning, signal processing, dynamical system or mathematical modelling To find
-
sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
-
to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
-
challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
-
, a state-of-the-art process-based model for groundwater risk assessment and contaminant transport modeling. By improving predictive modeling of transient contaminant source terms, this research will