This PhD position will be part of a larger strategic effort involving: the Faculty of Languages, the Disciplinary Domain of Humanities and Social Sciences, the faculty of Science and Technology, the Uppsala University Library and the Centre for Image Analysis. The focus will be on computerized image analysis with applications in Handwritten Text Recognition.
The Centre for Image Analysis (CBA) is a collaboration between Uppsala University and the Swedish University of Agricultural Sciences. Our purpose is to conduct research and education in computerized image analysis and perceptualization, both within image processing itself and to develop better methods, algorithms and systems for applications within primarily biomedicine and forest industry. CBA also aims to spread the knowledge about and encourage the use of image processing at other departments and in society. The Centre for Image Analysis is hosted at the Division of Visual Information and Interaction at the Department of Information Technology. There are approximately 250 employees at the department, including 100 teachers and 100 PhD students, and more than 3000 students are registered for one or more courses every year. For more information, see http://www.cb.uu.se/home.php and http://www.it.uu.se/?lang=en
Description of the subject area: The overall objective of the project is to develop methods for automatic analysis of digitized handwritten historical documents. The documents used for the project mainly come from the collections of Uppsala University Library and they are written in Latin or old Swedish.
Job assignment: To develop methods for large-scale handwritten text recognition applicable to a wide variety of historical documents. The developed methods are expected to make use of image analysis, language-modeling and machine learning, to improve state-of-the-art and to be used as tools by researchers within the humanities.
Qualification: The candidate must have an MSc degree in computer science, computational linguistics, mathematics or equivalent. Experience from programming and computerized image analysis is preferred. As the job assignment involves close interaction with researchers specialized in Handwritten Text Recognition (HTR), a background and/or strong interest in linguistics, history and languages such as Latin and Swedish is highly valued.
The position is for at most five years, and includes department duties (mainly teaching) at a level of at most 20%, as well as course participation. You will be expected to be able to teach in Swedish or English. Excellent skills in spoken and written English are an absolute requirement.
Rules governing Ph.D. Candidates are set out in the Higher Education Ordinance Chapter 5, § § 1-7, and in the Uppsala University's rules and guidelines, http://regler.uu.se/Rules_and_regulations_in_English/
The department is striving to achieve a more equal gender balance and female candidates are particularly invited to apply.
The application should include a description of your research interests, reasons for applying for this particular PhD position and past experience, a CV, copies of exams, degrees and grades, relevant publications, a copy of your MSc thesis (or a summary) and other relevant documents. Candidates are encouraged to provide letter(s) of recommendation and contact information to reference persons. We would also like to know the earliest possible date for starting. Please note that applications can only be accepted via the web interface linked below and not via email.
Further information about the position can be provided by Dr Anders Brun, anders@cb.uu.se, +46-18-4713473. The trade union representatives are Anders Grundström, Saco (the Swedish Confederation of Professional Associations), phone +46 18 471 5380 and Carin Söderhäll, TCO/ST (the Swedish Confederation of Professional Employees), phone +46 18 471 1996, Stefan Djurström, Seko (the Union of Service and Communication Employees), phone +46 18 471 3315.
You are welcome to submit your application no later than 31 of March 2013, marked with UFV-PA 2013/530. Use the link below to apply.
Application Deadline : 31 March 2013
