Are you an aspiring researcher and would you like to work on Natural Language Processing and Information Retrieval techniques to solve challenges in conversational intelligence? Start your academic career off right as a PhD candidate within the NWO-funded LESSEN project. Join a diverse team of researchers based at multiple Dutch universities and work with several industrial stakeholders to develop chat-based conversational agents.
The institute for Computing and Information Sciences (iCIS) at Radboud University is looking for a PhD candidate to work on the project "
LESSEN: Low Resource Chat-based Conversational Intelligence." The project aims to develop, implement and evaluate state-of-the-art safe and transparent chat-based conversational AI agents based on state-of-the-art neural architectures. The focus is on lesser resourced tasks, domains and scenarios.
The project is funded by an NWO Dutch Research Agenda grant awarded to a consortium consisting of the University of Amsterdam, Leiden University, the University of Groningen, Amsterdam University of Applied Sciences, Radboud University, Achmea, Albert Heijn, Bol.com, KPN, Rasa Technologies, Ahold Delhaize, and the Dutch national police force.
The aim of this PhD project is to generate synthetic data for training conversational agents. One of the limitations of developing models for conversational agents is the availability and cost of labelled training data. A common approach to alleviate this need is to increase the amount of training data by data augmentation. In this project, you will use knowledge graphs (e.g. Wikipedia) to develop methods that generate question-answer pairs that form coherent conversations.
You will work on the project under the supervision of a team consisting of Dr. Faegheh Hasibi (Radboud University), Prof. Evangelos Kanoulas (University of Amsterdam), and Prof. Arjen P. de Vries (Radboud University).
You will pursue your PhD in a vibrant international research environment in the data science group of iCIS at Radboud University, with top-notch professors and researchers in information retrieval and machine learning. iCIS values a diverse workforce. Female candidates are therefore particularly encouraged to apply. Your teaching load may be up to 10% of your appointment.