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AI & Machine Learning (neural engineering) PhD Projects, Programs & Scholarships

We have 16 AI & Machine Learning (neural engineering) PhD Projects, Programs & Scholarships

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Showing 1 to 10 of 16
  Computer aided design methods for mammalian genome engineering
  Research Group: Institute of Quantitative Biology, Biochemistry and Biotechnology
  Dr G Stracquadanio, Dr F Menolascina
Application Deadline: 5 January 2020

Funding Type

PhD Type

Computer Aided Design (CAD) software assists engineers in designing systems in-silico, thus reducing the time-to-market of a product and increasing the overall productivity.
  BioVision: bio-inspired computer vision using deep architectures (Advert Reference: SF19/EE/CIS/BELATRECHE)
  Dr A Belatreche, Dr F Khelifi
Applications accepted all year round

Funding Type

PhD Type

The primate visual system outperforms the existing automated vision systems in almost all measures.
  A Neural Fuzzy Fusion Engine for Human-Machine Autonomous Systems
  Dr YK Wang
Applications accepted all year round

Funding Type

PhD Type

Abstract. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS).
  Using ANN Technology to Determine Acceptable Microclimate Parameters for Heritage Preservation
  Research Group: Institute for Sustainable Building Design
  Dr F Wang
Application Deadline: 22 November 2019

Funding Type

PhD Type

Applications are invited for a 3.5-year ETP PhD studentship to conduct an experimental study using both Artificial Neural Network (ANN) modelling and mock-up testing.
  Slope stability and climate change in high-mountain regions: Understanding and predicting geo-hazards.
  Dr A Abellan, Dr B Murphy, Dr J West, Dr D Quincey
Application Deadline: 6 January 2020

Funding Type

PhD Type

HIGHLIGHTS. Timely project. a game changing approach to improve understanding, model and forecast landslides in mountainous areas is urgently needed.
  MRC DiMeN Doctoral Training Partnership: The role of tactile feedback from the foot in balance and gait across the lifespan
  Dr H Saal, Dr C Mazzà
Application Deadline: 6 January 2020

Funding Type

PhD Type

Tactile feedback from the foot sole has been shown to play an important role in balance and gait. However, feedback is impaired in ageing due to fiber loss and mechanical changes in the skin, leading to increased sway, unsteady gait, and risk of falling.
  Machine learning for nearshore wave prediction
  Dr E Medina-Lopez
Application Deadline: 9 January 2020

Funding Type

PhD Type

Co-Supervisor. Dr Rafael Bergillos, University of Cordoba. Co-Supervisor. Dr Ali Belmadani, Météo France Martinique. Summary. This project will investigate the prediction capabilities of nearshore wave conditions from offshore wave parameters and remotely sensed information, including satellite data and video imagery.
  PhD Position: Deep Reinforcement Learning for Computer Vision
  Research Group: Data Science
  Mr J Han, Prof G Montana
Applications accepted all year round

Funding Type

PhD Type

PROJECT OVERVIEW. Nowadays, machine learning, deep neural networks in particular, quickly become a viable means for solving real-life computer vision problems such as object detection, semantic segmentation, object recognition and tracking.
  Deep Learning based Network Forensic Methods for Investigating Botnets in the IoT (Application Ref: SF19/EE/CIS/ASLAM)
  Dr N Aslam, Dr B Issac
Applications accepted all year round

Funding Type

PhD Type

The process of designing IoT protocols and sensors and the lack of standards are the main reasons why the IoT is an easy target for botnets.
  Machine Learning for Computational Medical Imaging
  Dr M Golbabaee, Prof P Hall
Application Deadline: 8 December 2019

Funding Type

PhD Type

The University of Bath is inviting applications for a fully funded PhD studentship based in the Department of Computer Science and under the supervision of Dr Mohammad Golbabaee (lead supervisor) https://mgolbabaee.wordpress.com/ and Prof Peter Hall (co-supervisor) https://researchportal.bath.ac.uk/en/persons/peter-hall.
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