[PhD scholarship] Cluster Analysis for Functional Data
Mimi ZHANG
Location: Trinity College Dublin
School: School of Computer Science and Statistics
Funding amount: €24,500/year
Closing date: 30/Apr/2024
PhD starting time: 1st/Sep/2024
Project details: Functional data refer to a collection of functions that are continuous in both the independent and dependent variables. Examples include time series, trajectories, images, and other forms of data that are naturally represented as functions. Functional data clustering is to find patterns in the subjects, where each subject is represented by a continuous function. Functional data clustering has a wide range of applications in many fields: in bioinformatics to group gene expression profiles, in econometrics to group economic time series, and in engineering to group vibrations of mechanical systems. The main objectives of the PhD project are to develop innovative functional data clustering algorithms, code the algorithms into open software with well-designed documentation, and help maintain a digital platform for open (functional) data science.
You will be registered as a PhD in Statistics and physically hosted in the School of Computer Science and Statistics at Trinity College Dublin. You will be working under the guidance of Dr Mimi Zhang (https://www.tcd.ie/research/profiles/?profile=zhangm3).
Salary: The successful candidate will receive a full scholarship for a four-year structured PhD program. This scholarship covers all university fees for the duration of the program and includes a tax-free stipend of €24,500 per annum for four years. Additionally, a generous budget is provided to support conference travel, equipment, training, placement maintenance, and publication costs.
Candidate description: We are looking for candidates with a Bachelor's degree in statistics, math, computer science, or closely related subjects. A solid theoretical and practical knowledge of statistics is essential, along with proficiency in programming.
How to apply: Please submit your application here: https://forms.office.com/e/JjCKtYwiw8 Selected candidates will be contacted within 3 weeks after submission.