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Statistics (electrical) PhD Projects, Programs & Scholarships

We have 17 Statistics (electrical) PhD Projects, Programs & Scholarships

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  Computer Architectures for Probabilistic Robotics/Autonomous Systems Applications
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Computer Architectures for Probabilistic Robotics/Autonomous Systems Applications**.
  Approximate Bayesian methods for large scale imaging problems (EPS2020/41)
  Dr Y Altmann
Application Deadline: 28 February 2020

Funding Type

PhD Type

This project consists of investigating new approximate Bayesian methods for fast and robust estimation in high dimensional problem.
  Computational imaging: Multi-Sensors Fusion for High Resolution 3D Lidar videos (EPS2020/40)
  Dr AH Halimi, Prof S McLaughlin
Application Deadline: 28 February 2020

Funding Type

PhD Type

Recent technological innovations, eg detection and acquisition hardware, have pushed sparse-photon imaging to the fore in a variety of applications including 3D Lidar imaging and microscopy.
  Inequality, Health Beliefs, Networks and Inference: Exploring the Links Between Social Co-ordinates and Network Structure
  Prof N Jones
Applications accepted all year round

Funding Type

PhD Type

PhD Project. Imperial College Mathematics. Student Background. Theoretical Physics, Mathematics, Statistics, Electrical Engineering (BioMedical knowledge not required).
  Investigating Noise in Ageing Cellular Power Stations
  Prof N Jones
Applications accepted all year round

Funding Type

PhD Type

PhD Project. Imperial College Mathematics. Student Background. Theoretical Physics, Mathematics/Statistics, Electrical Engineering (Biological knowledge not required).
  Multimodal Deep Learning for Context Awareness (Application Ref: SF19/EE/CIS/WEI)
  Dr B Wei, Prof W L Woo
Applications accepted all year round

Funding Type

PhD Type

Context-awareness plays an essential role in a smart building, including many applications such as indoor localisation, activity recognition, identity recognition, etc.
  Centre for Doctoral Training in Interactive Artificial Intelligence

Funding Type

PhD Type

Fully Funded PhD Opportunities. Building on Bristol's world-leading expertise in AI and human-computer interaction, the Centre for Doctoral Training in Interactive Artificial Intelligence offers PhD studentships that will train you to become a leader in responsible human-in-the-loop AI systems.
  Hardware Implementations of Differential Privacy for Low-Power Energy-Scavenged Sensors
  Dr P Stanley-Marbell
Applications accepted all year round

Funding Type

PhD Type

The Physical Computation Laboratory is seeking a PhD student to work on a project developing new **Hardware Implementations of Differential Privacy for Low-Power Energy-Scavenged Sensors**.
  Anomaly Detection and Characterisation with Few-Shot Machine Learning
  Dr M Yaghoobi, Dr T Hospedales
Application Deadline: 31 July 2020

Funding Type

PhD Type

This PhD Studentship is sponsored by Thales UK and EPSRC. The successful candidate will seek to solve the problems faced by applying sparse data learning techniques for detection and classification to domains with very limited labelled data.
  KESS2 Scholarship: Techno-economic Analysis of Solar Heat Farms: Hydrogen, Water or Electricity? (MbyRes)
  Dr S Carr
Application Deadline: 1 March 2020

Funding Type

PhD Type

Here is an exciting opportunity to study the application of solar heat farms (based on arrays of solar thermal collectors and/or solar photovoltaic modules), which could lead to entirely new approaches to providing low carbon heat at scale.
  Artificial intelligence for smart engines
  Research Group: nCATS
  Dr L. Wang
Application Deadline: 31 August 2020

Funding Type

PhD Type

Project description.
  2019 Strathclyde SEA FindAPhD advert: Measuring security of Industry 4.0 systems
  Dr D Thomas
Applications accepted all year round

Funding Type

PhD Type

Introduction. Industry 4.0 will lead to many more critical industrial systems being Internet-connected and interdependent. Measuring the security of these distributed systems of industrial devices is vital to understand the risk of compromise this poses and to assess potential defences.
  Aircraft Electrification
  Research Group: Energy Systems
  Dr J Marco, Dr A Barai
Applications accepted all year round

Funding Type

PhD Type

PROJECT OVERVIEW. This fully funded PhD studentship represents a unique opportunity to undertake advanced characterisation, control system design and modelling research in close partnership with Vertical Aerospace (http://www.vertical-aerospace.com).
  Unbiased Estimation for Inverse Problems
  Dr A Jasra
Applications accepted all year round

Funding Type

PhD Type

This project concerns the development of Markov chain Monte Carlo and sequential Monte Carlo methods for unbiased estimation in Bayesian inverse problems.
  Statistical machine learning for efficient and reliable estimation in computationally intensive systems
  Dr X Chen
Application Deadline: 8 March 2020

Funding Type

PhD Type

A computationally intensive Industrial process is sometimes considered and modelled as a black-box system, for which one can only observe/analyse system’ inputs and outputs but with very limited knowledge of its internal mechanism.
  Towards prediction of synthetically accessible organic molecular crystals
  Dr V Kurlin, Prof A Cooper
Application Deadline: 15 March 2020

Funding Type

PhD Type

The vision of the project is to transform materials discovery into a routine computational task. Materials discovery still needs a lot of human expertise, trial-and-error and even pure luck, because there is no rigorous theory to guide an efficient search in the huge space of all theoretically possible materials.
  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).
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