Lead supervisor: Dr Peter Macgregor
Application deadline: 1 March 2025
Full details: https://blogs.cs.st-andrews.ac.uk/csblog/2024/11/14/fully-funded-phd-scholarship-in-algorithms-for-data-science/
Interested applicants are welcome to contact Dr Peter Macgregor (prm4@st-andrews.ac.uk) to discuss the project.
Project Description
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Modern data science and machine learning applications involve datasets with millions of data points and hundreds of dimensions. For example, deep learning pipelines produce massive vector datasets representing text, image, audio and other data types. The analysis of such datasets with classical algorithms often requires significant time and/or computational resources which may not be available in many applications.
This motivates the development of a new generation of fast algorithms for data analysis, running in linear or sub-linear time and often producing an approximate result rather than an exact one. Moreover, the dataset may change over time, requiring dynamic algorithms which handle updates efficiently.
This project will tackle aspects of the design, analysis, and implementation of algorithms for processing large dynamic datasets, with the aim to develop new algorithms with state-of-the-art practical performance and/or theoretical guarantees. This could involve performing new analysis of existing algorithms, designing new algorithms with provable guarantees, or implementing heuristic algorithms with state-of-the-art empirical performance.
Potential areas of research, depending on the interests of the candidate include
* nearest-neighbour search algorithms;
* clustering algorithms including hierarchical clustering, density-based clustering, and dynamic clustering;
* numerical linear algebra; and
* other projects in the area of algorithmic data science and machine learning.
Applicants should have a strong interest in the analysis of algorithms, knowledge of topics in discrete mathematics and linear algebra, and some familiarity with existing algorithms for data analysis and machine learning. Strong programming skills would also be desirable.
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