Continue with FacebookLooking to list your PhD opportunities? Log in here.
We have 14 anomaly detection PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
anomaly detection PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
We have 14 anomaly detection PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
PhD saved successfully
Anomaly Detection and Disease Classification in Electrocardiogram Signals using Advanced Signal Processing and 3D Image Classification
For provision of correct medicine, treatment and correct therapy, an accurate diagnosis is required. There are situations in which time-critical decisions need to be made to provide the right treatment to avoid long term morbidity or in some cases even death. Read more
Last chance to apply
L-Band TomoSAR Deep Imaging: From Glacier Internal Structure Mapping to Anomaly Detection - SENSE CDT
The Earth’s climate has changed through its history. A potential outcome of climate change is glacier melting, which is what we observe over the last decades. Read more
Driver intention analysis and anomaly detection for human-like automated driving vehicles
Automated driving technology is promising a safer transport future due to its potential to avoid human errors that are currently responsible for most road traffic accidents. Read more
A novel, secure, and cross platform Intrusion Detection System for protection of Critical National Infrastructure
Cyberattacks on Critical National Infrastructure (CNI) appear to be growing in occurrence and strength and Operational Technology (OT) networks have gradually become targets of attack for cyber criminals and state-sponsored hackers. Read more
Embedded time series machine learning
Supervisory Team. Tony Bagnall, Harold Chong. Project description. Sensors and embedded systems generate high-frequency and high-volume time series. Read more
Last chance to apply
Bayesian Meta-Learning for Earth Observation: Better Models with Less Data - SENSE CDT
Machine learning has brought significant improvements to pattern recognition systems in the past decade [5]. The three main factors that this success is attributed to are the use of deep neural networks, very large annotated training datasets, and abundant computing resources. Read more
PhD in Computing Science - Machine-learning based cyber resilience for the CNI
The Critical National Infrastructure (CNI) is becoming digitally enhanced and interconnected through the interface between Operational Technology (OT) with generic ICT capability. Read more
Self-supervised learning defending against advanced cyber threats in IoT [Self Funded Students Only]
Research Group:
Cybersecurity, Privacy and HCC Research Section
Machine learning techniques have been increasingly used in enhancing security by offering IoT systems anomaly detection, threats identification, malware detection, automated threat response, etc. Read more
Generative Deep Learning Models for Automated Craniofacial Surgical Planning
Aims of the Project. Implement a deep learning-based approach to detect and localise craniofacial anomalies in children. Develop a generative method to simulate a stereotypical paediatric skull from a skull with detected anomalies using a skull atlas as reference. Read more
PhD Studentship: Control methods for reliable sensing information in interconnected energy systems
Title: Control methods for reliable sensing information in interconnected energy systems. Duration of study: Full Time four-years fixed term. Read more
Security of Electric Vehicle Charging Infrastructure
The rise of Electric Vehicles (EVs) drives an increase in demand and rapid development of the charging infrastructure, where a charger interconnects with an EV and a charging provider as well as a site controller to authorise charging sessions and report any errors. Read more
Towards an Evolving Approach to Evaluate Security Monitoring Tools
With continuing growth in the size of computer networks and applications, the potential damage that can be caused is increasing. Intrusion detection is a common cyber security mechanism used to detect malicious activities in host and/or network environments. Read more
Cyber Security, Artificial Intelligence, Machine Learning and Blockchain Technology: Mitigating Cyber Attacks and Detecting Malicious Activities in Network Traffic
Research Group:
Applied Computing
Cyber attacks have become more widespread and several attacks have made headline news over the past decade, targeting industrial companies and governmental organisations. Read more
Machine learning solutions for computer network operations
We invite driven and enthusiastic PhD candidates to work in computer network operations and machine learning, in the Wolfson School of Mechanical, Electrical and Manufacturing Engineering at Loughborough University. Read more
- 1