We are seeking a PhD candidate in machine learning theory (statistical learning theory and deep learning theory) or theoretical-oriented topics, e.g., trustworthy machine learning, efficient machine learning. The project aims to theoretically understand why ML models perform well and/or design efficient and robust algorithms in trustworthy machine learning. The topics include but not limited to:

1. Statistical-computational gap in modern machine learning

2. Robustness of neural networks for trustworthy ML systems

3. Fine-tuning of modern machine learning models

The successful candidate is expected to have a solid background in applied mathematics/statistics/computer science or related discipline. Advanced coding skills are a big plus.

For further details please contact Dr. Fanghui Liu (fanghui.liu@warwick.ac.uk), Assistant Professor In Department of Computer Science at the University of Warwick. More information can be found on his homepage (www.lfhsgre.org).

We are seeking PhD candidates in the topic of Multiagent Systems and related areas, with particular emphasis on one or more of: computational social choice, algorithmic game theory, multiagent learning, and social and economic networks. The multiagent systems researchers at University of Warwick include Markus Brill, Debmalya Mandal, Ramanujan Sridharan, Long Tran-Thanh, and Paolo Turrini.

The expected starting date is October 2025 or as soon as possible thereafter. The deadline for our internal application round is 1 November 2024. To apply, please fill out the application form (which will ask you to upload a CV and a letter of motivation). We aim to have interviews between November 11th and 22nd, 2024. Top-ranked candidates will be put forward for a fully funded position through the Computer Science Centre for Doctoral Training and Research (CDT) by January 15th 2025.

Human activity recognition (HAR) is a compelling topic in the fields of ubiquitous computing, with numerous applications including human behaviour understanding, smart healthcare, human-computer-interaction (HCI), and more. Among various sensing technologies, Radio Frequency (RF) signals such as WiFi can be applied in a less intrusive manner, offering significant potential in smart home environments. However, due to multipath propagation, WiFi signals often contain a high level of noise from physical environments that need to suppressed before developing HAR models.