PhD Scholarship in Multimodal User Authentication and Personalization

at  Springer Nature

PHD SCHOLARSHIP IN MULTIMODAL USER AUTHENTICATION AND PERSONALIZATION

Employer
University of Galway (NUI Galway)
Location
Galway (County), Connacht (IE)
Salary
€22,000 annual stipend (tax-free). Tuition fees are paid
Closing date
29 Apr 2024
Discipline
Computing, Engineering
Job Type
PhD Position
Employment - Hours
Full time
Duration
Fixed term
Qualification
Masters
Sector
Academia

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DETAILED PROJECT DESCRIPTION

This is one of 3 Ph.D. positions on the PRIVI-SENSE project to reinvent today’s computational imaging as a privacy-secured method of sensing human subjects. Positions are available from Jan 2024.
This Ph.D. research topic will explore the extension of existing embedded, in-device authentication methods, based on conventional imaging, to employ methods based on multi-modal imaging data. An additional objective of this research will be to determine some unique advantages of multimodal authentication over conventional imaging and to personalize some of the sensing methods explored in the PRIVI-SENSE project. Based on our most recent research work, it is likely that this research topic will focus on the use of event-cameras combined with sparse/spiking neural network architectures for authentication and personalization.
A key end goal is to advance the use of smart-sensing in support of smart-city and smart-home use cases. This research will also contribution foundation techniques to the next generation of attentive computing – where computers will better understand the human they are interaction with. Note that C3I works with a number of industry partners and there will be opportunities for industry placements as part of this scholarship.
A more complete description of the project work and related Ph.D. and postdoctoral opportunities is available here: https://www.universityofgalway.ie/c3i/vacancies/
Living allowance (Stipend): €22,000 annual stipend (tax-free). Tuition fees are paid.
Academic Entry Requirements: Candidates must have a top honours grade in Electronic Engineering or Computer Science and completion of a relevant Masters degree or 5-year degree program is desirable.

In addition prospective candidates should have some background and experience in:

• State-of-Art Neural Architectures/Models for Computer Vision Fine-tuning or customization of one or more Neural Network Models (i.e. significant re-training or re-programming of the neural model)

Also Desirable to have experience in one or more of the following:

• Designing and running experiments with well-defined research outcomes Working with complex neural architectures (e.g. GANs, Transformers, Diffusion Models, etc) Working with multi-modal imaging data (e.g. NIR, LWIR or Event Cameras). Working on advanced data augmentation or learned augmentation techniques to support re-training of neural models Techniques for implementation of neural architectures on embedded systems or in hardware (e.g. FPGA, tinyML, network compression, sparsification, etc)

Contact Name: Prof. Peter Corcoran
Application Deadline: open until all positions filled
Primary Supervisor: Prof. Peter Corcoran

Please refer the Job description for details