Connectionists: Two PhD Positions at QMUL

[Timothy Hospedales]

Two PhD Positions at Queen Mary, University of London
School of Electronic Engineering & Computer Science

1. Machine Intelligence

The focus of this doctoral research project is on lifelong machine learning. Traditional machine learning methods learn each new problem from scratch, requiring extensive training each time. In contrast, humans rapidly learn to solve new and complex problems with limited practice by building on a lifetime of experience with related tasks and domains. The goal of this project is to develop models for lifelong machine learning, enabling experience from each encountered task and domain to be accumulated and exploited in the next. A variety of applications can be considered as lifelong machine learning impacts diverse areas including computer vision, security, forensics, medical diagnosis, big data, ecommerce and others. Fluency in English and a strong foundation in mathematics (linear algebra, calculus and statistics) and programming are essential. Machine learning and/or computer vision experience is a plus.

http://www.jobs.ac.uk/job/AFL430/phd-studentship-in-machine-intelligence/ 
For queries contact: Dr. Timothy Hospedales tmh at eecs.qmul.ac.uk.

2. Legal Reasoning

The focus of this doctoral research will be to address a key problem in the domain of legal reasoning: Bayesian statistics is playing an increasingly important role in many types of forensic evidence, but, problematically, the impact of the evidence is generally misunderstood and poorly presented by legal practitioners. The problem is exacerbated by a failure to consider or understand Bayes' theorem, which is the only rational to way to determine to impact of different pieces of evidence (this problem afflicts forensic experts as well as lawyers). The consequent misuse of statistical evidence has resulted in frequent miscarriages of justice, both in the UK and worldwide. This studentship will involve multidisciplinary research that includes the fields of cognitive psychology, statistics, data visualisation, as well as computer science. The research will address the problem of how non-experts in statistics can be presented with statistical evidence such that the evidence is comprehended and used correctly. Applicants must have a strong computational background, a solid understanding of Bayesian statistics, excellent writing skills, as well as an understanding or interest in human psychology.

http://www.jobs.ac.uk/job/AFL432/phd-studentship-in-risk-management-in-legal-reasoning/
For queries contact: Dr. Anne Hsu anne.hsu at eecs.qmul.ac.uk. 

Nationality: Open to all.
Deadline: 31 Jan 2013.
Interviews: Feb 2013.
Start: Sep 2013.

To Apply: http://www.eecs.qmul.ac.uk/phd/apply.php