The PhD project focuses on hybrid natural language processing, which combines deep learning and knowledge-based approaches. The goal of the project is to develop and evaluate interpretable deep learning models for information extraction for disaster response.
This project is embedded within the NWO-funded project ‘InDeep: Interpreting deep learning models for language, speech and music‘. This project is a collaboration with several universities and companies in the Netherlands. The project’s consortium brings together a number of pioneering experts in the field of interpretability and aims at bridging the gap between the latest academic advances and societal and industrial users of deep learning models.
The PhD project focuses on hybrid natural language processing, which combines deep learning and knowledge-based approaches. The goal of the project is to develop and evaluate interpretable deep learning models for information extraction for disaster response.
As a PhD candidate, you will have the opportunity to work together with Floodtags, a company that monitors online media for information about floods and wildfires. Disaster events (floods, earthquakes, explosions) often occur without prior warning. However, today’s social media offers an opportunity to quickly gather direct information about an unfolding crisis since people on location use mobile phones to inform others about the situation. Organisations such as the Red Cross actively use these information channels to keep informed about ongoing events. Offline analysis of media content can also be useful for disaster management, since it would benefit from having accurate historical overviews of the regions that are likely to be flooded, or hit by typhoons or earthquakes. By analysing the impact of past disaster events, it is possible to create risk profiles of these areas. Such overviews are currently non-existent, particularly in developing countries.
We offer a position that combines PhD research (0.8 FTE) with teaching (0.2 FTE). During the course of the PhD, you will have the opportunity to obtain a university teaching qualification.
Profile
- You hold a Research Master’s degree in Artificial Intelligence, Computer Science or Data Science (or a related discipline).
- You have good knowledge of machine learning.
- Practical experience with deep learning models and toolkits is an advantage.
- You have followed one or more courses on linguistics and/or text mining and/or natural language processing.
- You have experience with experimental evaluation, including developing datasets and analysing errors in order to improve machine learning models.
- You are interested in or have knowledge of Tagalog.
- You have excellent oral and writing skills in English; knowledge of Dutch would be an advantage.
- You are able to work independently and flexibly, taking initiative where needed. You are able to communicate and collaborate effectively in a team setting.
- You are interested in and committed tot teaching and supervising Bachelor’s students.
We are
The Faculty of Arts is committed to knowledge production with a significant scientific and social impact. With over 500 academic and support staff, we teach and conduct research in the fields of history and art, languages and cultures, and linguistics and communication, using innovative methodologies and working in close collaboration between the disciplines. Our research is embedded in two research institutes: the Centre for Language Studies (CLS) and the Radboud Institute for Culture & History (RICH). We currently have approximately 2,500 students, enrolled in three departments: the Department of History, Art History and Classics, the Department of Modern Languages and Cultures, and the Department of Language and Communication. We aim to contribute to a more sustainable and inclusive world, which is why we especially seek applications from candidates who bring diverse perspectives, backgrounds, and skills that will be assets to our study programmes and research profiles.
Radboud University
We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 24,000 students and 5,600 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!
We offer
- Employment for 1.0 FTE.
- The gross starting salary amounts to €2,443 per month based on a 38-hour working week, and will increase to €3,122 in the fourth year (salary scale P).
- You will receive 8% holiday allowance and 8.3% end-of-year bonus.
- You will be employed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years (4 year contract).
- You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
- Working for us means getting extra days off. In case of full-time employment, you can choose between 29 or 41 days of annual leave instead of the legally allotted 20.
Additional employment conditionsWork and science require good employment practices. This is reflected in Radboud University’s primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.
Would you like more information?
For questions about the position, please contact Iris Hendrickx, Asisstant Professor at +31 243 61 57 75 (Wednesday and Thursday) or iris.hendrickx@ru.nl.
Practical information and applications
You can apply until 2 May 2022, exclusively using the button below. Kindly address your application to Iris Hendrickx. Please fill in the application form and attach the following documents:
- A letter of motivation.
- Your CV, including the contact details of two academic references.
The first round of interviews will be held on Monday 16 May. The second round of interviews will be held on Monday 23 May. The starting date is either 1 July 2022 or 1 September 2022, depending on your preference.
We can imagine you’re curious about our application procedure. It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates.
We drafted this vacancy to find and hire our new colleague ourselves. Recruitment agencies are kindly requested to refrain from responding.