57 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" PhD scholarships in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Employer
- University of Exeter
- University of Exeter;
- Swansea University
- University of Birmingham;
- University of Cambridge
- The University of Manchester
- University of Birmingham
- University of Nottingham
- University of Sheffield
- Loughborough University
- Newcastle University
- UNIVERSITY OF VIENNA
- University of Bristol
- University of Warwick
- Abertay University
- Imperial College London;
- The Open University;
- The University of Edinburgh;
- The University of Manchester;
- UCL
- University of Bristol;
- University of Cambridge;
- University of East Anglia
- University of East Anglia;
- University of Essex
- University of Nottingham;
- University of Strathclyde (UOS)
- 17 more »
- « less
-
Field
-
. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
-
. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
-
, and advanced machine learning in the engineering domain. Generative AI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase
-
-resolution (SR) technologies influence human and machine-based facial identification. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: 1. Do SR
-
an allied field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning
-
Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
-
structures, access to space, multidisciplinary design and concurrent engineering, uncertainty treatment and optimisation, machine learning. (https://www.strath.ac.uk/ ) Task description for your Individual
-
to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
-
, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse
-
: · Learning how to express software requirements precisely using formal models. · Using these specifications to automatically generate test cases for software systems and code. · Exploring how test