Jobs

PhD students in the field of digital history and hermeneutics

The Individual and Collective Reasoning Group ICR at the Computer Science and Communications research unit of the University of Luxembourg, led by Prof. Leon van der Torre, is looking for a:

• PhD student (doctoral candidate) in Applied Knowledge Representation and Reasoning

with a special interest in one or several of the following areas (see also appendix):
- Text mining via NLP aimed at argument structures in legal and scientific texts
- Formal and computational modeling of legal and scientific debates (diachronic)
- Knowledge representation and reasoning in historical sciences

• Ref: R-STR-3067-00-B
• Starting date: as soon as possible
• Duration: 3 years (14+22-months contract, 40h/week), further extendable by 1 year if required.
• Doctoral student status at the University of Luxembourg
• No deadline for applications: applications will be handled as they arrive

The student will be attached to the interdisciplinary Doctoral Training Unit “Digital History and Hermeneutics“ (DTU DHH) and participate in the activities of ICR and the DTU DHH (see: http://www.dhlab.lu/digital-literacy/digital-history-hermeneutics-dtu/).

ICR is doing research on
• Logic and Knowledge representation
• Deontic reasoning, Natural language processing (for legal applications, in the context of the project MIREL: http://www.mirelproject.eu)
• Formal argumentation, Belief revision
• Artificial Intelligence, Intelligent agents

Your Role

• Writing a doctoral dissertation in the relevant area
• Presentation of research findings at workshops and conferences
• Publication of scientific papers in peer-reviewed international journals
• Moderate participation in teaching activities

For further inquiries please contact Prof. Leon van der Torre: leon.vandertorre@uni.lu

Your Profile

• A Master degree in Computer Science or a related discipline.
• Dedication to actively participate in the interdisciplinary framework of the DTU and the ICR
• Solid background in knowledge representation and reasoning and in one or several of the areas of interest
• Strong analytical capacity, creativity, and commitment
• Good written and spoken English skills.

Our Offer

• The University of Luxembourg offers a very international, dynamic, and well-connected research environment
• Financial support (travel allowances) for participating in scientific activities (workshops, conferences, summer schools, etc.
• Attractive salary and employment contract including social insurance
• Enrolment in a doctoral school and attachment to the DTU DHH
with an interesting offer of various disciplinary and interdisciplinary courses and digital skills trainings

Application Documents (in English):

• Letter of motivation which must contain
- an explanation of the motives for participating in the DTU and of expected learning outcomes and career perspectives
- a short sketch of a research project that fits the interests of ICR and at least one of the thematic axes developed in the DTU
- a motivation for the choice of the main supervisor (Prof. Leon van der Torre) • Full CV
• Transcript of academic records (including grades) and copies of diplomas
• Names of at least two references willing to write a letter of recommendation (they may be contacted by us)

All applications should be sent to leon.vandertorre@uni.lu.

Deadline: no specific deadline is set. We are looking for a candidate as soon as possible.

Further Information:

• Scientific questions should be addressed directly to Prof. Leon van der Torre (leon.vandertorre@uni.lu)

• Administrative questions should be sent to pride-gsm@uni.lu

The University of Luxembourg is an equal opportunity employer and applications by women are especially encouraged.

APPENDIX

In recent years, the analysis of argumentation using NLP techniques, so-called argumentation mining, has gained a lot of attention in the computational linguistics research community and has been applied to a number of domains, from student essays to scientific articles and online user-generated content. It belongs to the tool set of the Digital Humanities (DH), which are born of the encounter between traditional humanities and computational methods. Curation, analysis, editing, and modeling comprise fundamental activities at the core of Digital Humanities. Computational argumentation tools can be relevant for the study of past political, scientific, or legal debates debates and of the repercussions of such claims in an historical and comparative perspective. In order to find argumentation patterns in political speeches, typically covering a wide range of issues from international politics, legal controversies, to environmental challenges, the application of computational methods to assist scholars in qualitative analysis is advisable.

Large amounts of text are added to the Web daily from social media, web-based commerce, scientific papers, eGovernment consultations, etc. Such texts are used to make decisions in the sense that people read the texts, carry out some informal analysis, and then make a more or less reasonable decision; for example, a consumer might read the comments on an Amazon website about a camera before deciding what camera to buy. The problem is that the information is distributed, unstructured, and not cumulative but possibly conflicting. In addition, the argument structure - justifications for a claim and criticisms - might be implicit or explicit within some document, but harder to discern across documents. The sheer volume of information overwhelms even expert users. Given all these problems, reasoning about arguments on the web is currently a big challenge. To address then, one may try to develop tools to aggregate, synthesize, structure, summarize, and reason about arguments in texts. Such tools would enable users to search for particular topics and their justifications, trace through the argument (justifications for justifications and so on), as well as to systematically and formally reason about the graph of arguments. By doing so, a user would have a better, more systematic basis for making a decision. However, deep, manual analysis of texts is time-consuming, knowledge intensive, and thus unscalable. To acquire, generate, and transmit the arguments, we need scalable machine-based or machine-supported approaches to extract arguments. The application of tools to mine arguments would be very broad and deep given the variety of contexts where arguments appear and the purposes they are put to.

References:
- Proceedings of the Workshop on Frontiers and Connections between Argumentation Theory and Natural Language Processing http://ceur-ws.org/Vol-1341/
- Lippi, M., Torroni, P., Argumentation Mining: State of the Art and Emerging Trends, ACM Transactions on Internet Technology, 2015.
- Available resources for Argument mining http://argumentationmining.disi.unibo.it/resources.html

The Historical Institute / Center for Contemporary and Digital History University of Luxembourg has obtained a large grant from the Fonds National de la Recherche Luxembourg in the framework of the so-called PRIDE-program, enabling the creation of a Doctoral Training Unit (DTU) and opens up to 13 positions for PhD students (Doctoral candidates) in the field of digital history and hermeneutics (m/f).

This DTU aims at creating an experimental trading zone for the reflection on the epistemological and methodological challenges of doing digital history / humanities research in an interdisciplinary setting. All PhD students will have to conduct their research within the conceptual framework of the DTU. Participation in the collectively organized skills trainings on digital literacy as well as active participation in the planning and organization of thematic workshops of the DTU will be required. For a detailed description of the DTU and the thematic axes see: http://www.dhlab.lu/digital-literacy/digital-history-hermeneutics-dtu/