83 algorithm-"Multiple"-"Prof" "NTNU Norwegian University of Science and Technology" PhD positions in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; Swansea University
- ; The University of Manchester
- ; Edge Hill University
- ; Newcastle University
- ; University of Birmingham
- ; University of Leeds
- ; University of Cambridge
- ; University of Exeter
- ; University of Southampton
- KINGS COLLEGE LONDON
- The University of Manchester
- University of Cambridge
- ; Cranfield University
- ; Lancaster University
- ; The University of Edinburgh
- ; University of Bristol
- ; University of East Anglia
- ; University of Nottingham
- ; University of Oxford
- ; University of Sheffield
- ; University of Surrey
- The University of Edinburgh
- University of Birmingham
- University of Bristol
- University of Exeter
- University of Newcastle
- University of Warwick
- 20 more »
- « less
-
Field
-
address: Dr Fahad Panolan: f.panolan@leeds.ac.uk Project summary The Algorithms group at the University of Leeds (UK) is offering a fully funded 3.5-year PhD studentship on Parameterized Complexity and
-
integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
-
from multiple sources to estimate air quality, along with associated measures of uncertainty. Some traditional models can be relatively restrictive in nature and lack capabilities to deal with large
-
context. The work will include, but is not limited to: investigating new mathematical formulations of the underlying physics; developing fast algorithms and numerical methods that leverage modern parallel
-
physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
-
control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
-
capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
-
the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
-
, integrity-aware multi-domain navigation benchmark and associated algorithms, tested in realistic operational environments. The outputs will support standardisation efforts, accelerate cross-domain navigation
-
objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as