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We have 73 complex networks PhD Projects, Programmes & Scholarships



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complex networks PhD Projects, Programmes & Scholarships

We have 73 complex networks PhD Projects, Programmes & Scholarships

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Novel stochastic control method for a class of complex networks

Complex systems, which contain large ensembles of elements interacting with each other and are affected by noises and uncertainties, have become one of the major research fields due to their presence in the real life. Read more

Correlation ensembles in complex networks

The project is centred on characterizing a new type of complex network ensemble. In studying complex systems, researchers often use graph-sampling methods to build networks obeying given constraints, such as a degree sequence or a joint-degree matrix (JDM). Read more

Realising the potential of data games to keep humans in the loop for the analysis of large and complex data sets in population health sciences

Population health science requires understanding a large and increasing amount of complex data, from complete human genomes and causal networks of the aetiology of disease, to open and unstructured data about community response to rapidly changing public health challenges. Read more

Autonomous Drone Surveys and Convolutional Neural Networks for Bridge Maintenance: A Predictive Approach Using Finite Element Analysis

Objective. The primary objective of this research is to develop a comprehensive framework for bridge maintenance that integrates autonomous drone surveys, convolutional neural networks (CNNs), and Finite Element analysis. Read more

Synthesis of Chemical Reaction Networks Prioritising Sustainability (ALBERT CDT)

What is ALBERT?. Doctoral Training in Autonomous Robotic Systems for Laboratory Experiments. A cohort of students will be part of a mini, pilot Centre for Doctoral Training (CDT) focused on developing the science, engineering, and socio-technology that underpins building robots required for laboratory automation, e.g. Read more

Next-Generation Spiking Neural Networks Architectures and Machine Learning Algorithms

Spiking Neural Networks (SNNs) represent the so called ‘third generation’ of artificial neural network models, that bridge the gap between neuroscience and artificial intelligence by relying on biologically realistic models of neurons and network architectures to carry out computations. Read more

Neural Networks for Complex Dynamical Systems

Details. Dynamical systems are often solved/integrated by a suitable numerical discretisation method in such a way that certain properties of the underlying systems will be preserved. Read more

Structure evolution in complex alloys by analysis of combinatorial complexes

The last couple of decades have been a period of active development and manufacture of new complex-structured bulk materials, such as TWIP steels, nickel superalloys and high-entropy alloys for novel applications in energy and transport industries. Read more

Advancing Non-reversibility in Bayesian Networks [Self-Funded Students Only]

  Research Group: Visual Computing
About the Project. Bayesian Sampling has been very well studied in the literature for investigating various complex time series and regression analysis problems up to date. Read more

Machine learning and statistical modelling of trans-omic networks in controlling cell identity, cell-fate decisions, and cancers

The advances in mass spectrometry-based proteomics and phosphoproteomics, and next-generation sequencing-based transcriptomics and epigenomics create the opportunity to study cell identity, cell-fate decisions, and complex diseases such as cancers at a system level. Read more

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