Doctoral grants area of Machine/deep learning, language technology, computer vision for enriching heritage collections
The Departments of Literature and Linguistics (Faculty of Arts and Philosophy) of the University of Antwerp and the Montefiore Institute (Faculty of Applied Sciences) of the University of Liège are seeking to fill two full-time (100%) vacancies for
Doctoral Grants in the area of machine/deep learning, language technology, and/or computer vision for enriching heritage collections
The two positions are available within the framework of the INSIGHT (Intelligent Neural Systems as InteGrated Heritage Tools) project, funded by the Belgian Science Policy Office. This project unites academic partners from Liège and Antwerp with stakeholders from the heritage sector (Royal Museums of Fine Arts / Art and History, Brussels). The project focuses on multimodal applications of “deep” representation learning to enrich and improve access to heritage collections and push boundaries in computational art history.
The Platform for Digital Humanities in the University of Antwerp engages with multiple aspects of the application of computing technologies in the Humanities. The CLiPS research center focuses on the application of statistical and machine learning methods in language technology. Scholars in the department of literature focus on the application of X-technologies and Machine Learning in literary studies. The department of Electrical Engineering and Computer Science of the University of Liège has developed a strong expertise in machine learning and its application in various fields such as computer vision. In this latter domain, ULg partners involved in the project have developed the opensource Cytomine platform for advanced image analysis.
Job description
- You prepare a doctoral thesis in the field of machine/deep learning, language technology, and computer vision in the context of heritage studies.
- You publish scientific articles related to the research project of the assignment.
- You contribute to teaching and research in the host departments.
Profile and requirements
- You hold a master degree in a field, broadly relevant to Digital Humanities, Art History, Computer Science, Linguistics, Computer Vision, and/or Machine Learning.
- You can submit outstanding academic results.
- Foreign candidates are encouraged to apply.
- You are quality-oriented, conscientious, creative and cooperative.
- The ideal candidate will have demonstrable, first-hand experience in Machine Learning for computer vision or for Language Technology (in the Digital Humanities), in particular distributional semantics (word embeddings) and representation learning.
- You have an excellent knowledge of academic English. Knowledge of Dutch or French is not required but is an asset for the project.
- The ideal candidate has demonstrable experience in a programming language such as Python, and ideally also deep learning frameworks, such as Tensorflow or PyTorch.
- The ideal candidate will have a broad interest in heritage, the GLAM sector and/or art history. The focus in your teaching corresponds to the educational vision of the university.
- Your academic qualities comply with the requirements stipulated in the university’s policy.
- You are quality-oriented, conscientious, creative and cooperative.
We offer
- a doctoral scholarship for a period of two years, with the possibility of renewal for a further two-year period after positive evaluation;
- the start date of scholarship will be 1 October, 1 November or 1 December 2017 or 1 January 2018;
- a dynamic and stimulating work environment. One PhD student is expected to be mainly located in Antwerp and the other one in Liège, with exchange stays planned between the two Universities. Double doctoral degrees will be envisaged;
- a dynamic and stimulating work environment.
How to apply?
- Applications should be submitted by 15 September 2017 by email (to mike.kestemont@uantwerp.be and p.geurts@ulg.ac.be) and should include a copy of your CV, a cover letter and, if available, a research paper / MA thesis and a link to the candidate’s portfolio page, with code samples, on a site such a GitHub.
- For application or questions about the profile and the description of duties, please contact Prof. Mike Kestemont, mike.kestemont@uantwerp.be
For more information please click "Further Official Information" below.
This opportunity has expired. It was originally published here:
https://www.uantwerpen.be/en/jobs/vacancies/ap/2017bapflwef265/