Fully funded PhD position on Knowledge Representation for Learning and Uncertainty

University of Edinburgh

Application deadline: 9 December 2016 (**see below for more information**)

The overall goal of this project is to develop new methods and formal languages that can effectively bridge the areas of knowledge representation, probabilistic reasoning and machine learning. Formal languages and symbolic techniques have a long and distinguished history in AI, and have widely impacted many scientific and commercial endeavors in diverse areas such as verification, robotics, planning, logistics and human-level commonsense reasoning. However, many of the applications in these areas often need to handle inherent uncertainty, complemented by an increased prominence of data-oriented algorithms and statistical techniques. From a foundational perspective, the question of how knowledge representation languages need to be augmented to handle these complex notions of uncertainty is an open and challenging one. From a practical perspective, enriching existing machine learning algorithms by human-readable representations and background knowledge can be very useful. For sample PhD projects, see http://bit.ly/2f4tYS5

This position is an opportunity to combine cutting edge research at the intersection of knowledge representation and machine learning.
We envision the application of these methods to challenging problems arising in logistics, planning, robotics and commonsense reasoning.

Background Required
The project is suitable for a student with a top MSc or first-class bachelor's degree in computer science, mathematical logic, statistics, physics, or a related numerate discipline.
Previous coursework or experience in machine learning and mathematical logic/knowledge representation is desirable, although we do not expect students to have both of these.
We envision the development of new software tools that demonstrate the languages and methods involved, and the application of these methods to challenging problems arising in logistics, planning, robotics and/or commonsense reasoning. Therefore, a programming background is desirable. 

Why Edinburgh 
The School of Informatics at the University of Edinburgh has one of the largest concentrations of computer science research in Europe, with over 100 faculty members and 275 PhD students. The school is particularly strong in the research area of artificial intelligence. Our strength in these areas have been recognized by award of EPSRC Centre for Doctoral Training in Data Science. The University of Edinburgh is one of the founding partners of the Alan Turing Institute, the UK's national research institute for data science.

Funding Information
The scholarship consists of an annual bursary up to a maximum of three years. Overseas applicants are advised to apply before the standard informatics deadlines and apply for other scholarships. See http://www.ed.ac.uk/schools-departments/informatics/postgraduate/fees  and http://www.ed.ac.uk/informatics/postgraduate/apply/key-dates.

Application Information
For informal enquiries about the position, please contact Vaishak Belle <vaishak@ed.ac.uk>. Formal application must be through the School's normal PhD application process: http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=494

For more information on CISA, see http://web.inf.ed.ac.uk/cisa/study-with-us 

For full consideration, please apply by Dec 9, 2016.

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