PhD candidate in deep learning for natural language processing
Faculty of Science – Institute for Logic, Language and Computation
- 10 juli 2017
- Master's degree
- €2,222 to €2,840 gross per month
- 31 juli 2017
- 38 hours per week
The position is for a joint project between the Institute for Logic, Language and Computation (ILLC) and the Institute of Informatics (IvI). The PhD candidate will spend much of the time posted at the Institute for Language, Cognition and Computation (ILCC) at the University of Edinburgh, where the project leader holds his main faculty appointment.
The Institute for Logic, Language and Computation (ILLC) is a research institute at the University of Amsterdam, in which researchers from the Faculty of Science and the Faculty of Humanities collaborate. Its central research area is the study of fundamental principles of encoding, transmission and comprehension of information. Research at ILLC is interdisciplinary, and aims at bringing together insights from various disciplines concerned with information and information processing, such as logic, mathematics, computer science, linguistics, cognitive science, artificial intelligence, musicology and philosophy. Research is organized in three research groups: Logic and Computation (LoCo), Logic and Language (LoLa) and Language and Computation (LaCo). Check here for an overview of the research being carried out in the different groups. For the research carried out by the individual staff members of ILLC, see their personal pages via People at ILLC.
The Informatics Institute is one of the large research institutes with the faculty, with a focus on complex information systems divided in two broad themes: 'Computational Systems' and 'Intelligent Systems.' The Amsterdam Machine Learning Lab (AMLAB) of IvI conducts research in the area of large scale modelling of complex data sources. This includes the development of new methods for probabilistic graphical models and nonparametric Bayesian models, the development of faster (approximate) inference and learning methods, deep learning, causal inference, reinforcement learning and multi-agent systems and the application of all of the above to large scale data domains in science and industry ('Big Data problems').
ILCC (University of Edinburgh) is a leading research institute for computational approaches to language (spoken and written), cognition and communication. There are over 10 faculty members at ILCC conducting basic and applied research in computational linguistics and natural language processing. For further information about ILCC please refer to this page.
Deep learning has been very successful in a number of areas (e.g., computer vision, speech processing and natural language processing). However, there has been little work on developing deep learning methods for predictive analysis of complex network data (e.g., social networks, trading networks etc.). This project fills this gap and focuses on statistical modelling of information exchange in transaction networks. In this work we will use very large amounts of real data from a trading network (an industrial partner) but the methods will generalize to other types of networks where heterogeneous data is being exchanged (e.g., social networks). We will be developing predictive algorithms relying on the flow of transactions in the network (e.g., various types of recommendations as well as detection of novel and significant events). We also seek to cluster the businesses trading over the networks as well as the products that are being traded. As information in these networks mostly comes in a textual form, we will develop methods for inducing predictive semantics representations of texts relying both on the text itself but also on the flow of information in the network.
This PhD vacancy will focus primarily on deep learning for natural language processing (affiliated with ILLC, supervised by Dr. Ivan Titov)
Close collaboration between the PhD candidate and other members of the team (including Prof. Max Welling and the other PhD candidate within the project, Thomas Kipf, both at IvI) is envisaged. Also collaboration with members of Ivan Titov’s team at the University of Edinburgh, and well as with other members of the Institute for Cognition, Language and Computation of the University of Edinburgh, is expected and encouraged.
The PhD candidate will be expected to fulfil the following tasks:
- complete and defend a PhD thesis within the official appointment duration of four years;
- regularly present intermediate research results at international workshops and conferences, and publish them in proceedings and journals;
- collaborate with researchers in other relevant parts of ILLC (Amsterdam), ILCC (Edinburgh) and IvI (Amsterdam) as well as with the industrial partner providing the data;
the PhD candidate is also expected to assist in teaching of bachelor and master students.
Necessary qualifications for candidates include excellent grades, proven research talent, affinity with machine learning, statistics and excellent programming skills. A master’s degree in computer science (preferably with a specialization in artificial intelligence and/or machine learning), applied mathematics or computational linguistics. Strong programming skills are required.
Candidates are expected to have an excellent command of English, and good academic writing and presentation skills.
Applicants are kindly requested to motivate why they have chosen to apply for this position.
The applicant should be willing and able spend much of their time posted at the University of Edinburgh.
For further information please contact:
Appointment (1,0 fte) is on a temporary basis for a period of four years. An initial contract will be given for 18 months. If positively evaluated, the contract will be extended for a further 30 months. On the basis of a full-time appointment (38 hours per week), the gross monthly salary amounts to €2,222 during the first year, rising to €2,840 during the final year.
The Collective Labour Agreement for Dutch Universities is applicable.
Starting date: as soon as possible.
Applications should include the following information, in separate pdf files (not zipped), using surname, initials and a self-evident word as file names, e.g., Smith J CV:
- a curriculum vitae (including an url for download of M.Sc. thesis -- if relevant);
- a letter of motivation (at most 1 page) explaining why you are interested in this position;
- a research statement (at most 2 pages), explaining your research interests and experience;
- a list of all graduate courses taken, with a transcript of grades;
- the names and contact details of two or three references who can provide further details about you.
Completed applications should be submitted by 31 July 2017 to email@example.com and should state your name and vacancy number 17-363 in the subject field. The committee cannot guarantee that late or incomplete applications will be considered. #LI-DNP
No agencies please