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Mathematics (brain) PhD Projects, Programs & Scholarships

We have 15 Mathematics (brain) PhD Projects, Programs & Scholarships

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  PhD studentship in Engineering/Physics/Neuroscience/Medicine/Maths/Chemical Engineering to work on Imaging brain and nerve function with Electrical Impedance Tomography.
  Prof D Holder, Dr K aristovich
Application Deadline: 21 September 2019

Funding Type

PhD Type

Background. Electrical Impedance Tomography is a new medical imaging method which enables images of the internal electrical impedance of a subject to be produced with arrays or external electrodes.
  Unifying multiscale brain network interactions (SAMIU19FMHMTH)
  Dr S Sami, Dr D Proment
Application Deadline: 31 October 2019

Funding Type

PhD Type

Important. Applications for this project will open on the UEA system w/c 2 September 2019. We offer a fully funded inter-disciplinary PhD project that focuses on the development of new mathematical models and their application in cognitive and clinical neuroscience.
  Research on Exoskeleton Control System based on Brain-Computer Interface
  Dr M Huang, Dr R Yang, Dr D Tate, Dr R Ferrero
Applications accepted all year round

Funding Type

PhD Type

To ensure the safe and reliable operation of exoskeleton, the control system based on brain-computer interface is the premise and foundation, which has been discussed in literature.
  Developing a new learning algorithm for biologically inspired spiking neural networks
  Dr A Taherkhani, Prof TM McGinnity, Dr G Cosma
Applications accepted all year round

Funding Type

PhD Type

The brain’s processing ability to solve complex problems has inspired many researchers to investigate how the brain processes information, reasons and its learning mechanisms.
  Self-organisation as a theory of brain development
  Dr SP Wilson, Dr JV Stone
Applications accepted all year round

Funding Type

PhD Type

Self-organisation is a general theory of how function is assigned to cortical microcircuits. The theory predicts that a balance between cooperative and competitive interactions in local cortical circuits, consolidated by Hebbian learning, results in similar inputs being represented by nearby neurons.
  Machine Learning; Data Mining
  Prof A Balinsky
Applications accepted all year round

Funding Type

PhD Type

Deep Learning is another name for a set of algorithms that use a neural network as an architecture.
  Neuronal Dynamics from a complex network perspective
  Prof A Politi, Dr E Ullner
Applications accepted all year round

Funding Type

PhD Type

The human brain is possibly the most intriguing complex system we know. The combination of experimental work and theoretical approaches has gained many insides in the last century but we are still far away from a real understanding.
  Bridging the interface between time series analysis and network science
  Research Group: Complex Systems and Networks
  Dr L Lacasa
Applications accepted all year round

Funding Type

PhD Type

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2019 for students seeking funding, or at any point in the academic year for self-funded students.
  Developing Theoretical Frameworks to Solve Outstanding Network Theory and Data Science Algorithms
  Research Group: Complex Systems and Networks
  Dr G Bianconi
Applications accepted all year round

Funding Type

PhD Type

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2019 for students seeking funding, or at any point in the academic year for self-funded students.
  Network modelling of spatial distributions from large data sets
  Research Group: Complex Systems and Networks
  Dr V Nicosia
Applications accepted all year round

Funding Type

PhD Type

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2019 for students seeking funding, or at any point in the academic year for self-funded students.
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