Deadline: 31 Jan. 2013
Applications are invited for a PhD Studentship starting in September 2013 within the Risk Information
Management group. 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.
The studentship will be based in the School of Electronic Engineering and Computer Science (EECS)
www.eecs.qmul.ac.uk at Queen Mary University of London, in the Risk and Information Management
Group,which has a world-leading reputation in the area of risk assessment. The RIM group undertakes
interdisciplinary research in decision analysis and risk, databases/information retrieval, personalisation, learning, uncertainty, and Bayesian methods. Much of the research involves combining data and human expertise to create intelligent solutions for high stakes decisions. We work with practitioners to produce intelligent ‘unified models’ (typically causal Bayesian networks) that use both data and expertise as inputs, to support expert decision making in multiple application domains. The group is currently working on improved decision making in medical, legal, systems engineering, security and safety applications.
This studentship, funded by a Queen Mary Prinicipal’s studentship, is for 3 years and will cover student fees and a tax-free stipend starting at £15,590 per annum. Candidates should have a first class honours degree or
equivalent, or a strong Masters Degree, in computer science, mathematics, physics or electronic engineering. For queries about the studentship please contact Dr. Anne Hsu anne.hsu@eecs.qmul.ac.uk.
To apply please follow the on-line process (see www.qmul.ac.uk/postgraduate/apply ) by selecting
“Computer Science” in the “A-Z list of research opportunities” and following the instructions on the right
hand side of the web page.
Please note that instead of the 'Research Proposal' we request a 'Statement of Research Interests'. Your
Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area?
(ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper. Mark clearly the statement with Your Name and the title “Risk Management in Legal Reasoning”. In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at: www.eecs.qmul.ac.uk/phd/apply.php
Applications are invited for a PhD Studentship starting in September 2013 within the Risk Information
Management group. 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.
The studentship will be based in the School of Electronic Engineering and Computer Science (EECS)
www.eecs.qmul.ac.uk at Queen Mary University of London, in the Risk and Information Management
Group,which has a world-leading reputation in the area of risk assessment. The RIM group undertakes
interdisciplinary research in decision analysis and risk, databases/information retrieval, personalisation, learning, uncertainty, and Bayesian methods. Much of the research involves combining data and human expertise to create intelligent solutions for high stakes decisions. We work with practitioners to produce intelligent ‘unified models’ (typically causal Bayesian networks) that use both data and expertise as inputs, to support expert decision making in multiple application domains. The group is currently working on improved decision making in medical, legal, systems engineering, security and safety applications.
This studentship, funded by a Queen Mary Prinicipal’s studentship, is for 3 years and will cover student fees and a tax-free stipend starting at £15,590 per annum. Candidates should have a first class honours degree or
equivalent, or a strong Masters Degree, in computer science, mathematics, physics or electronic engineering. For queries about the studentship please contact Dr. Anne Hsu anne.hsu@eecs.qmul.ac.uk.
To apply please follow the on-line process (see www.qmul.ac.uk/postgraduate/apply ) by selecting
“Computer Science” in the “A-Z list of research opportunities” and following the instructions on the right
hand side of the web page.
Please note that instead of the 'Research Proposal' we request a 'Statement of Research Interests'. Your
Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area?
(ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper. Mark clearly the statement with Your Name and the title “Risk Management in Legal Reasoning”. In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at: www.eecs.qmul.ac.uk/phd/apply.php
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