Publisher
source

Prof J Sweeney

1 year ago

Gaussian Processes for Non-Linear Modelling with application to Battery State Estimation University of Limerick in Ireland

Degree Level

PhD

Field of study

Computer Science

Funding

Fully Funded

Deadline

Expired

Country flag

Country

Ireland

University

University of Limerick

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Where to contact

Official Email

Keywords

Computer Science
Data Science
Machine Learning
Mathematics
Artificial Intelligence
Gaussian Processes
Statistics
physicss
Applied statistics
Statistical Science

About this position

One full-time 4-year structured PhD position is available in the Department of Mathematics & Statistics at the University of Limerick, Ireland. The project is fully funded including fees and a tax-free stipend (currently €22,000 but under review upwards, not including additional tutorial payments). Expenses for computing equipment and a generous budget for conference travel and materials are also provided.

The PhD student will develop advanced statistical machine learning approaches (exploring for eg the potential of deep gaussian processes) for application in the research field of battery technology. This programme is in conjunction with Analog Devices, Inc. (NASDAQ: ADI). Concentrated contact with ADI researchers is a key aim of the research project, allowing the student to observe research outputs being actioned in industry settings. It is also envisaged that, subject to visa requirements and funding, the studentship will include a placement at the Analog Garage Research Lab in Boston, MA, USA.

The ideal candidate for this project is a student with an undergraduate (or preferably MSc) degree in statistical science, mathematics, computer science, or physics. In the first 12 months, the student will undertake training through several research projects focused on developing expertise in the field of Gaussian processes and application of neural networks (learning by doing), attending workshops, and mandatory PhD training in research skills provided by the University.

Informal queries and applications (cv & cover letter) can be sent to Prof. James Sweeney at .

Funding details

Fully Funded

How to apply

? Informal queries and applications (cv & cover letter) can be sent to Prof. James Sweeney at [email protected].

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