Position:	PhD student position in Computer Vision
Institution:	Universität Basel
Location:	Basel, Switzerland
Duties:	The PhD dissertation project will focus on how to experimentally capture hypothetical ductus (stroke order and direction of writing) reconstructed by experts and to design deep learning pipelines as well as experimental protocols to acquire and compare ductus reconstitutions. In addition, the PhD student will take part in the team's discussions on the history and evolutions of Greek handwritings across a millennium. She/he will help organize; jointly with the team; a number of workshops and conferences, participate in outreach activities of the project and present her/his research at scientific meetings
Requirements:	Applicants should hold a Master's degree in Computer Vision or related fields with grades above average (Master's thesis must be completed by the start of the position), be highly motivated to conduct innovative transdisciplinary research at the intersections of Artificial Intelligence, Kinematics, Digital Humanities and Ancient History, have an excellent command of at least English, and be able to work autonomously within an internationally and institutionally diverse environment
Text:	PhD student position in Computer Vision The PhD dissertation project will focus on how to experimentally capture hypothetical ductus (stroke order and direction of writing) reconstructed by experts and to design deep learning pipelines as well as experimental protocols to acquire and compare ductus reconstitutions. In addition, the PhD student will take part in the team's discussions on the history and evolutions of Greek handwritings across a millennium. She/he will help organize; jointly with the team; a number of workshops and conferences, participate in outreach activities of the project and present her/his research at scientific meetings Applicants should hold a Master's degree in Computer Vision or related fields with grades above average (Master's thesis must be completed by the start of the position), be highly motivated to conduct innovative transdisciplinary research at the intersections of Artificial Intelligence, Kinematics, Digital Humanities and Ancient History, have an excellent command of at least English, and be able to work autonomously within an internationally and institutionally diverse environment

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