Category Archives: News

Minh Le and Antske Fokkens’ long paper accepted for EACL 2017

Title: Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing

Conference: EACL 2017 (European Chapter of the Association for Computational Linguistics), at Valencia, 3-7 April 2017.

Authors: Minh Le and Antske Fokkens Title: Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency ParsingTackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing by Minh Le and Antske Fokkens

Abstract:
Error propagation is a common problem in NLP. Reinforcement learning explores erroneous states during training and can therefore be more robust when mistakes are made early in a process. In this paper, we apply reinforcement learning to greedy dependency parsing which is known to suffer from error propagation. Reinforcement learning improves accuracy of both labeled and unlabeled dependencies of the Stanford Neural Dependency Parser, a high performance greedy parser, while maintaining its efficiency. We investigate the portion of errors which are the result of error propagation and confirm that reinforcement learning reduces the occurrence of error propagation.

Papers accepted at COLING 2016

Two papers from our group have been accepted at the 26th International Conference on Computational Linguistics COLING 2016, at Osaka, Japan, from 11th to 16th December 2016.

sushi_COLING

Semantic overfitting: what ‘world’ do we consider when evaluating disambiguation of text? by Filip Ilievski, Marten Postma and Piek Vossen

Abstract
Semantic text processing faces the challenge of defining the relation between lexical expressions and the world to which they make reference within a period of time. It is unclear whether the current test sets used to evaluate disambiguation tasks are representative for the full complexity considering this time-anchored relation, resulting in semantic overfitting to a specific period and the frequent phenomena within.
We conceptualize and formalize a set of metrics which evaluate this complexity of datasets. We provide evidence for their applicability on five different disambiguation tasks. Finally, we propose a time-based, metric-aware method for developing datasets in a systematic and semi-automated manner.

More is not always better: balancing sense distributions for all-words Word Sense Disambiguation by Marten Postma, Ruben Izquierdo and Piek Vossen

Abstract
Current Word Sense Disambiguation systems show an extremely low performance on low frequent senses, which is mainly caused by the difference in sense distributions between training and test data. The main focus in tackling this problem has been on acquiring more data or selecting a single predominant sense and not necessarily on the meta properties of the data itself. We demonstrate that these properties, such as the volume, provenance and balancing, play an important role with respect to system performance. In this paper, we describe a set of experiments to analyze these meta properties in the framework of a state-of-the-art WSD system when evaluated on the SemEval-2013 English all-words dataset. We show that volume and provenance are indeed important, but that perfect balancing of the selected training data leads to an improvement of 21 points and exceeds state-of-the-art systems by 14 points while using only simple features. We therefore conclude that unsupervised acquisition of training data should be guided by strategies aimed at matching meta-properties.

LREC2016

CLTL papers, oral presentations, poster & demo sessions at LREC2016: 10th edition of the Language Resources and Evaluation Conference, 23-28 May 2016, Portorož (Slovenia)

LREC2016 Language Resources and Evaluation Conference, 23-28 May 2016, Portorož Slovenia

LREC2016 Conference Programme

Monday 23 May 2016

11.00 – 11.45 (Session 2: Lightning talks part II)
Multilingual Event Detection using the NewsReader Pipelines”, by Agerri R, I. Aldabe, E. Laparra, G. Rigau, A. Fokkens, P. Huijgen, R. Izquierdo, M. van Erp, Piek Vossen, A. Minard, B. Magnini

Abstract
We describe a novel modular system for cross-lingual event extraction for English, Spanish,, Dutch and Italian texts. The system consists of a ready-to-use modular set of advanced multilingual Natural Language Processing (NLP) tools. The pipeline integrates modules for basic NLP processing as well as more advanced tasks such as cross-lingual Named Entity Linking, Semantic Role Labeling and time normalization. Thus, our cross-lingual framework allows for the interoperable semantic interpretation of events, participants, locations and time, as well as the relations between them.

Tuesday 24 May 2016

09:15 – 10:30 Oral Session 1
Stereotyping and Bias in the Flickr30k Dataset” by Emiel van Miltenburg

Abstract
An untested assumption behind the crowdsourced descriptions of the images in the Flickr30k dataset (Young et al., 2014) is that they “focus only on the information that can be obtained from the image alone” (Hodosh et al., 2013, p. 859). This paper presents some evidence against this assumption, and provides a list of biases and unwarranted inferences that can be found in the Flickr30k dataset. Finally, it considers methods to find examples of these, and discusses how we should deal with stereotypedriven descriptions in future applications.

Day 1, Wednesday 25 May 2016

11:35 – 13:15 Area 1 – P04 Information Extraction and Retrieval
NLP and public engagement: The case of the Italian School Reform” by Tommaso Caselli, Giovanni Moretti, Rachele Sprugnoli, Sara Tonelli, Damien Lanfrey and Donatella Solda Kutzman

Abstract
In this paper we present PIERINO (PIattaforma per l’Estrazione e il Recupero di INformazione Online), a system that was implemented in collaboration with the Italian Ministry of Education, University and Research to analyse the citizens’ comments given in #labuonascuola survey. The platform includes various levels of automatic analysis such as key-concept extraction and word co-occurrences. Each analysis is displayed through an intuitive view using different types of visualizations, for example radar charts and sunburst. PIERINO was effectively used to support shaping the last Italian school reform, proving the potential of NLP in the context of policy making.

15:05 – 16:05 Emerald 2 – O8 Named Entity Recognition
Context-enhanced Adaptive Entity Linking” by Giuseppe Rizzo, Filip Ilievski, Marieke van Erp, Julien Plu and Raphael Troncy

Abstract
More and more knowledge bases are publicly available as linked data. Since these knowledge bases contain structured descriptions of real-world entities, they can be exploited by entity linking systems that anchor entity mentions from text to the most relevant resources describing those entities. In this paper, we investigate adaptation of the entity linking task using contextual knowledge. The key intuition is that entity linking can be customized depending on the textual content, as well as on the application that would make use of the extracted information. We present an adaptive approach that relies on contextual knowledge from text to enhance the performance of ADEL, a hybrid linguistic and graph-based entity linking system. We evaluate our approach on a domain-specific corpus consisting of annotated WikiNews articles.

16:45 – 18:05 – Area 1 – P12
GRaSP: A multi-layered annotation scheme for perspectives” by Chantal van Son, Tommaso Caselli, Antske Fokkens, Isa Maks, Roser Morante, Lora Aroyo and Piek Vossen

Abstract / Poster
This paper presents a framework and methodology for the annotation of perspectives in text. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenomena through different annotation initiatives. We propose an annotation scheme that integrates these different phenomena. We use a multilayered annotation approach, splitting the annotation of different aspects of perspectives into small subsequent subtasks in order to reduce the complexity of the task and to better monitor interactions between layers. Currently, we have included four layers of perspective annotation: events, attribution, factuality and opinion. The annotations are integrated in a formal model called GRaSP, which provides the means to represent instances (e.g. events, entities) and propositions in the (real or assumed) world in relation to their mentions in text. Then, the relation between the source and target of a perspective is characterized by means of perspective annotations. This enables us to place alternative perspectives on the same entity, event or proposition next to each other.

18:10 – 19:10 – Area 2 – P16 Ontologies
The Event and Implied Situation Ontology: Application and Evaluation” by Roxane Segers, Marco Rospocher, Piek Vossen, Egoitz Laparra, German Rigau, Anne-Lyse Minard

Abstract / Poster
This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology is built on top of existing resources such as WordNet, SUMO and FrameNet. The ontology is injected to the Predicate Matrix, a resource that integrates predicate and role information from amongst others FrameNet, VerbNet, PropBank, NomBank and WordNet. We illustrate how these resources are used on large document collections to detect information that otherwise would have remained implicit. The ontology is evaluated on two aspects: recall and precision based on a manually annotated corpus and secondly, on the quality of the knowledge inferred by the situation assertions in the ontology. Evaluation results on the quality of the system show that 50% of the events typed and enriched with ESO assertions are correct.

Day 2, Thursday 26 May 2016

10.25 – 10.45 – O20
Addressing the MFS bias in WSD systems” by Marten Postma, Ruben Izquierdo, Eneko Agirre, German Rigau and Piek Vossen

Abstract
This paper presents a framework and methodology for the annotation of perspectives in text. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenomena through different annotation initiatives. We propose an annotation scheme that integrates these different phenomena. We use a multilayered annotation approach, splitting the annotation of different aspects of perspectives into small subsequent subtasks in order to reduce the complexity of the task and to better monitor interactions between layers. Currently, we have included four layers of perspective annotation: events, attribution, factuality and opinion. The annotations are integrated in a formal model called GRaSP, which provides the means to represent instances (e.g. events, entities) and propositions in the (real or assumed) world in relation to their mentions in text. Then, the relation between the source and target of a perspective is characterized by means of perspective annotations. This enables us to place alternative perspectives on the same entity, event or proposition next to each other.

11.45 – 13.05 – Area 2 – P25
The VU Sound Corpus: Adding more fine-grained annotations to the Freesound database” by Emiel van Miltenburg, Benjamin Timmermans and Lora Aroyo

Day 3, Friday 27 May 2016

10.45 – 11.05 – O38
Temporal Information Annotation: Crowd vs. Experts” by Tommaso Caselli, Rachele Sprugnoli and Oana Inel

Abstract
This paper describes two sets of crowdsourcing experiments on temporal information annotation conducted on two languages, i.e., English and Italian. The first experiment, launched on the CrowdFlower platform, was aimed at classifying temporal relations given target entities. The second one, relying on the CrowdTruth metric, consisted in two subtasks: one devoted to the recognition of events and temporal expressions and one to the detection and classification of temporal relations. The outcomes of the experiments suggest a valuable use of crowdsourcing annotations also for a complex task like Temporal Processing.

12.45 – 13.05 – O42
Crowdsourcing Salient Information from News and Tweets” by Oana Inel, Tommaso Caselli and Lora Aroyo

Abstract
The increasing streams of information pose challenges to both humans and machines. On the one hand, humans need to identify relevant information and consume only the information that lies at their interests. On the other hand, machines need to understand the information that is published in online data streams and generate concise and meaningful overviews. We consider events as prime factors to query for information and generate meaningful context. The focus of this paper is to acquire empirical insights for identifying salience features in tweets and news about a target event, i.e., the event of “whaling”. We first derive a methodology to identify such features by building up a knowledge space of the event enriched with relevant phrases, sentiments and ranked by their novelty. We applied this methodology on tweets and we have performed preliminary work towards adapting it to news articles. Our results show that crowdsourcing text relevance, sentiments and novelty (1) can be a main step in identifying salient information, and (2) provides a deeper and more precise understanding of the data at hand compared to state-of-the-art approaches.

14:55 – 16:15 – Area 2- P54
Two architectures for parallel processing for huge amounts of text” by Mathijs Kattenberg, Zuhaitz Beloki, Aitor Soroa, Xabier Artola, Antske Fokkens, Paul Huygen and Kees Verstoep

Abstract
This paper presents two alternative NLP architectures to analyze massive amounts of documents, using parallel processing. The two architectures focus on different processing scenarios, namely batch-processing and streaming processing. The batch-processing scenario aims at optimizing the overall throughput of the system, i.e., minimizing the overall time spent on processing all documents. The streaming architecture aims to minimize the time to process real-time incoming documents
and is therefore especially suitable for live feeds. The paper presents experiments with both architectures, and reports the overall gain when they are used for batch as well as for streaming processing. All the software described in the paper is publicly available under free licenses.

14:55 – 15:15 Emerald 1 – O47
Evaluating Entity Linking: An Analysis of Current Benchmark Datasets and a Roadmap for Doing a Better Job” by Marieke van Erp, Pablo Mendes, Heiko Paulheim, Filip Ilievski, Julien Plu, Giuseppe Rizzo and Joerg Waitelonis

Abstract
Entity linking has become a popular task in both natural language processing and semantic web communities. However, we find that the benchmark datasets for entity linking tasks do not accurately evaluate entity linking systems. In this paper, we aim to chart the strengths and weaknesses of current benchmark datasets and sketch a roadmap for the community to devise better benchmark datasets.

15.35 – 15.55 – O48
MEANTIME, the NewsReader Multilingual Event and Time Corpus” by Anne-Lyse Minard, Manuela Speranza, Ruben Urizar, Begoña Altuna, Marieke van Erp, Anneleen Schoen and Chantal van Son

Abstract
In this paper, we present the NewsReader MEANTIME corpus, a semantically annotated corpus of Wikinews articles. The corpus consists of 480 news articles, i.e. 120 English news articles and their translations in Spanish, Italian, and Dutch. MEANTIME contains annotations at different levels. The document-level annotation includes markables (e.g. entity mentions, event mentions, time expressions, and numerical expressions), relations between markables (modeling, for example, temporal information and semantic role labeling), and entity and event intra-document coreference. The corpus-level annotation includes entity and event cross-document coreference. Semantic annotation on the English section was performed manually; for the annotation in Italian, Spanish, and (partially) Dutch, a procedure was devised to automatically project the annotations on the English texts onto the translated texts, based on the manual alignment of the annotated elements; this enabled us not only to speed up the annotation process but also provided cross-lingual coreference. The English section of the corpus was extended with timeline annotations for the SemEval 2015 TimeLine shared task. The First CLIN Dutch Shared Task at CLIN26 was based on the Dutch section, while the EVALITA 2016 FactA (Event Factuality Annotation) shared task, based on the Italian section, is currently being organized.

Master’s Evening, Dec. 01 2015

Master’s Evening 1 december 2015

On Tuesday 1 December 2015 you can visit our Master’s Evening where you can get informed about most of our Master’s degree programmes during information sessions. Please register and choose which of these sessions you would like to attend.

Date: Tuesday 1 December 2015
Time: 17:00 – 20:30
For whom: Higher education students and professionals
Location: Main building VU Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam

Please find information on our Research Master Specialization ‘Linguistic Engineering’

If you are not able to attend our Master’s Evening on 1 December 2015, you can visit the Master’s Day on Saturday 12 March 2016 or find out more about VU Amsterdam and our study programmes:
• Find your international Master’s degree programme and contact the coordinator for questions
Meet VU Amsterdam representatives in your own country
Visit our international students Facebook

Press release VU University on NewsReader: Join the hackathon!

VU-hoogleraar en Spinozawinnaar Piek Vossen presenteert NewsReader
Ontdek ook zelf deze nieuwe technologie die het nieuws leest

In 2013 startte Piek Vossen (hoogleraar computationele lexicologie), samen met onderzoekers in Trento en San Sebastian en met de bedrijven LexisNexis (NL), SynerScope (NL) en het Engelse ScraperWiki het NewsReader project om een computerprogramma te ontwikkelen dat dagelijks het nieuws ‘leest’ en precies bijhoudt wat, wanneer, waar gebeurd is in de wereld en wie er bij betrokken is. Het project kreeg hiervoor 2,8 miljoen euro subsidie van de Europese Commissie.

SynerScope‘s visualization: extraction from 1.26M news articles

Nieuws lezen in vier talen
In afgelopen 3 jaar hebben de onderzoekers een technologie ontwikkeld om de computer automatisch het nieuws te laten lezen in vier talen. Uit miljoenen krantenartikelen is nu een doorzoekbare database gemaakt waarin duplicaten zijn ontdubbeld, complementerende informatie uit verschillende berichten op een slimme manier samengevoegd is en is de informatie verrijkt met fijnmazige types zodat je niet alleen op persoonsnamen zoals ‘Mark Rutte’ en `Diederik Samsom’ kunt zoeken, maar ook op entiteiten van het type ‘politicus’.

Presentatie NewsReader
Op dinsdagmiddag 24 november 2015 organiseert de onderzoeksgroep Computational Lexicology & Terminology Lab (CLTL) van Piek Vossen een workshop waarin de eindresultaten van het project gepresenteerd worden. Ook zijn er diverse sprekers die hun visie op het project geven, zoals VU-hoogleraar Frank van Harmelen (Knowledge Representation & Reasoning), Bernardo Magnini, onderzoeker bij FBK in Trento en Sybren Kooistra, data journalist bij de Volkskrant en medebedenker en hoofredacteur van Yournalism, het platform voor onderzoeksjournalistiek.

Doe mee met de Hackathon!
Op 25 november kunnen gebruikers zelf aan de slag met de nieuwsdatabase die is opgebouwd uit miljoenen krantenartikelen. Meer informatie en aanmelden.

NewsReader Workshop & Hackathon, Nov. 24—25 2015

Car Wars: Industrial Heroes Going Down Fighting

On 24 and 25 November 2015, we will showcase the NewsReader project and invite you to come explore our technology and its results yourself during our NewsReader Workshop and Hackathon.

Event Details
We have developed a powerful new tool called ‘NewsReader’ which utilises natural language understanding and semantic web technology. This helps you to better understand the interactions between companies and key individuals, derived from news articles.
Our dataset encompasses 12 years of news charting the struggle of automotive players to rule the global market, to satisfy the expectations of the shareholders, and their suffering from the financial crisis and new economies: industrial heroes going down!

The Workshop
Tuesday 24 November 2015, 14:00 – 18:00 Amsterdam Public Library
In this workshop, we will bring together start-ups, companies, researchers and developers to present and discuss the NewsReader project, the technological domains it draws from and future applications for these technologies.
This afternoon will feature invited talks, demos, a panel discussion and a networking reception.
Confirmed Speaker:
Prof. dr. Frank van Harmelen, Vrije Universiteit Amsterdam. Frank van Harmelen is a professor in Knowledge Representation & Reasoning in the AI department (Faculty of Science) at the Vrije Universiteit Amsterdam. After studying mathematics and computer science in Amsterdam, he moved to the Department of AI in Edinburgh, where he was awarded a PhD in 1989 for his research on meta-level reasoning.

The Hackathon
Wednesday 25 November 2015, 10:00 – 18:00 Amsterdam Public Library
In June 2014 and January 2015 we ran several hackathons in both London and Amsterdam in which NewsReader enabled the attendees to pull out networks of interactions between entrepreneurs, politicians, companies and thoroughly test drive our technology. This November, we’re releasing a new version of our processing pipeline and we’re scaling up to 10 million processed news articles from sources about the automotive industry to obtain a searchable database of the news. At the hackathon, you can play with this dataset and explore the processing pipeline.
The global automotive industry has a value in the order of $1 trillion annually. The industry comprises a massive network of suppliers, manufacturers, advertisers, marketeers and journalists. Each of these players has his/her own story, often with unexpected origins or endings; one day you may be CEO of a big car company, the next you are out and making pizzas. With NewsReader, you can uncover these stories to reconstruct the past.

This event may be of interest to you if:
You’re interested in natural language processing and/or semantic web technology
You’re a data journalist on an automotive desk;
You’re an analyst sifting daily news looking for information on your company or on competitors;
You’re a data analyst looking to understand how your customers operate their supply chain
You’re an analyst trying to find secondary events that could influence an investment decision;
You’re interested in visualising big data

Attendance is free, but please register by Sunday 22 November 17:00 CET. .

NewsReader helps you find a needle in a haystack.
#NewsReader

VENI grant for Antske Fokkens

Antske Fokkens received a VENI grant for her proposal Reading between the lines. The project aims at identifying so-called implicit perspectives in text.

Perspectives are conveyed in many ways. Explicit opinions or highly subjective terms are easily identified. However, perspectives are also expressed more subtly. For instance, Nick Wing argues that media describe white suspects (e.g. brilliant, athletic) more positively than black victims (e.g. gang member, drug problems). Ivar Vermeulen (p.c.) observes in a small Dutch corpus that Moroccan perpetrators are easily called thieves (implying generic behavior), where other perpetrators from Dutch only stole something (implying incidental behavior). These observations are anecdotal, but reveal how choices concerning what information to include or how to describe someone’s role may display a specific perspective.

This project will investigate how linguistic analyses may be used to identify these more implicit ways of expressing perspectives in text. This research will be carried out in three stages: First, large scale corpus analyses will be applied to identify distributions of semantic roles (what entities do) and other properties assigned to them (their characteristics). In the second stage, generic participants will be linked to the semantic role they imply (e.g. a thief will be linked to the perpetrator of stealing). With these links, we can investigate whether thieves are described differently from people who steal. In the third stage, emotion and sentiment lexica will be used to identify the sentiment associated with descriptions of people enabling research that investigates whether people are depicted positively or negatively.

The research is carried out in the context of digital humanities and social sciences. Evaluation and experimental setup will be guided towards identifying differences in perspective between sources. In addition to correctness of linguistic analyses (intrinsic evaluation), the possibility of using the method for identifying changes in perspective over time (historic research) or differences in perspective between sources (communication science) will be investigated.

VU University scientists cluster responses NWO’s National Research Agenda

Led by Piek Vossen, a group of scientists at VU University automatically divided 11,700 questions from NWO’s National Research Agenda into clusters. On the basis of language technology and mathematical equations of the most important words, there were slightly over 60 clusters of questions found which at their turn were classified in a few hundred sub-clusters. Important themes are health and energy, but also big data, art, and sports. NWO is happy with this analysis. The VU Topic Browser allows NWO to quickly and efficiently process the large number of responses.

National Science Agenda VU Topic Browser — by Emiel van Miltenburg, Kasper Welbers, Hennie van der Vliet, Wouter van Atteveldt, Piek Vossen
National Science Agenda VU Topic BrowserNational Science Agenda VU Topic Browser The graph shows 60 clusters and a few hundred sub-groups found in 11,700 questions from NWO’s National Research Agenda.

Netherlands Organisation for Scientific Research (NWO): Dutch Science Agenda
Scientists determine the Dutch Science Agenda together with companies, civil society organisations and interested citizens. The agenda consolidates the themes that science will focus on in the coming years. What are the favourable opportunities for Dutch science and how can science contribute to finding solutions for societal challenges and making the most of economic opportunities?

Position AAA Data Science Postdoc or PhD Student in Computational Linguistics

We are hiring: Postdoctoral researcher/PhD candidate in Computational Linguistics

AAA Data Science Postdoc or PhD Student in Computational Linguistics

The Amsterdam Academic Alliance (AAA) is a joint initiative of the two Amsterdam-based universities – VU and the UvA – aimed at intensifying collaboration with each other and with other knowledge institutions in the region. The objective of the AAA is to cement Amsterdam’s position as a major international player and hub of academic excellence. The alliance is to result in different outcomes in each scientific field.

This advertisement concerns one of the 14 positions. The Network Institute of the VU University of Amsterdam is looking for a motivated Postdoctoral researcher or PhD student for the project “From text to Deep Data”. The candidate will be part of the Network Institute of the VU University Amsterdam and will work within multidisciplinary teams of humanities researchers and computer scientists.
The work will be done in the context of a larger research program called “QuPiD2: Quality and Perspectives in Deep Data” in collaboration with other researchers aiming all together to achieve a formal modeling of quality and perspectives.

As part of the QuPiD2 research team, the candidate will develop 1) a perspective model for representing the subjective relation between the source of information and the statements in it, and 2) software to detect such interpersonal communication layers and perspectives from text. The project will transform big unstructured text data into deep data that show the emotions, opinions and view points on the changing world. It will reveal the social networks and dynamics within trust networks that influence our world views.

Tasks
1. Studying existing models for handling provenance, attribution, sentiments, opinions and emotions as expressed in text.
2. Developing an overarching perspective model for representing the subjective relations between sources and their statements. The model will initially be based on textual data but should show the capacity to model perspectives on any type of (big) data.
3. Using semantic web standards, e.g. RDF, SPARQL, to represent and access the data within the project
4. Studying existing NLP approaches to detect perspective relations in texts. Both English and Dutch texts will be considered.
5. Developing a machine-crowd empowered processing of textual sources for populating the QuPiD2 model
6. Creating data sets for training and evaluation through expert annotation and crowd annotation.
7. Developing new components and approaches to obtain the perspective values within the model from textual data.
8. Evaluate the components against the data sets developed and within an application environment.
9. Collaboration with the QuPiD2 program research team
10. Publish the results of the work as scientific articles in high ranked journals and conferences, as well as present the work at relevant scientific venues

Requirements
The candidate should have a strong background (MA) in computational linguistics and semantic web technology with expertise in data modelling, modelling perspectives, subjectivity and attribution relations expressed in natural language. The candidate should have sufficient programming skills and experience with data engineering and text mining.

Further particulars
The appointment will be for a period of three years for a postdoc and four years for a PhD student. You can find information about our excellent employment conditions at www.workingatvu.nl such as:
• Remuneration of 8,3% end-of-year bonus and 8% holiday allowance;
• Solid pension scheme (ABP);
• A minimum of 29 holidays In case of full-time employment;
• Possibilities to save up holidays for sabbatical leave.

Salary
For a postdoc, the salary will be in accordance with university regulations for academic personnel, and depending on experience, range from a minimum of € 2,476 gross per month up to a maximum of € 3,908 gross per month (salary scale 10) based on a full-time employment.

For a PhD student, the salary will be in accordance with university regulations for academic personnel, range from a minimum of € 2,125 gross per month in the first year up to a maximum of € 2,717 (salary scale 85.0-3) based on full-time employment.

Information
For additional information please contact:
Prof. Piek Vossen
phone: +31 681773878 or +31 20 59 86457
e-mail: info@cltl.nl / attention Piek Vossen
website: http://www.cltl.nl

Dr. Lora Aroyo
Phone: +31 620329972
e-mail: lora.aroyo@vu.nl
website: http://lora-aroyo.org, http://wm.cs.vu.nl

Application
Applications may only be submitted via informatica.secretariaat.few@vu.nl. To process your application immediately, please quote the vacancy number and the title of the position you are applying for in the subject-line. Applications must include a detailed curriculum vitae, a motivation letter explaining why you are the right candidate, list of projects you have worked on with brief descriptions of your contributions and the names and contact addresses of two academic references from which information about the candidate can be obtained. All these should be grouped in one PDF attachment.

Applications will be accepted until 10 May 2015.

Any other correspondence in response to this advertisement will not be dealt with.