PhD position in Deep Learning

I have a fully funded PhD position in deep learning.

Deep neural networks, a.k.a. deep learning, have transformed the fields of computer vision, speech recognition and machine translation, and now rivals human-level performance in a range of tasks. While the idea of neural networks dates several decades back, their recent success is attributed to three key factors: (1) vast computational power, (2) algorithmic advances, and (3) the availability of massive amounts of training data.
There is no doubt that deep learning will continue to transform other fields as well, including that of information retrieval. One major challenge is that for most information retrieval tasks, training data is not available in huge quantities. This is unlike, for example, to object recognition, where there are large scale resources at one’s disposal to train neural networks with (tens of) millions of parameters (e.g., the ImageNet database contains over 14 million images).

Deep learning is inspired by how the brain works. Yet, humans can learn and generalize from a very small number of examples. (A child, for example, does not need to see thousands of instances of cats, in many different sizes and from numerous different angles, to be able to recognize a cat and tell it apart from a dog.) Can deep neural networks be enhanced with this capability, i.e., to be able to learn and generalize from sparsely labeled data? The aim of this project is to answer this question, specifically, in the application domain of information retrieval.

Details and application instructions can be found here.
Application deadline: March 26, 2017.

Important note: there are multiple projects advertised within the call. You need to indicate that you are applying for this specific project. Feel free to contact me directly for more information.

PhD vacancy

I am looking for a PhD student to work on understanding complex information needs.

Web search engines have become remarkably effective in providing appropriate answers to queries that are issued frequently. However, when it comes to complex information needs, often formulated as natural language questions, responses become much less satisfactory (e.g., “Which European universities have active Nobel laureates?”). The goal of this project is to investigate how to improve query understanding and answer retrieval for complex information needs, using massive volumes of unstructured data in combination with knowledge bases. Query understanding entails, among others, determining the type (format) of the answer (single fact, list, answer passage, list of documents, etc.) and identifying the series of processing steps (retrieval, filtering, sorting, aggregation, etc.) required to obtain that answer. If the question is not understood or ambiguous, the system should ask for clarification in an interactive way. This could be done in a conversational manner, similarly to how it is done in commercial personal digital assistants, such as SIRI, Cortana, or Google Now.

The successful applicant would join a team of 2 other PhD students working on the FAETE project.

Details and application instructions can be found here.
Application deadline: April 17, 2016.

Important note: there are multiple projects advertised within the call. You need to indicate that you are applying for this specific project. Feel free to contact me directly for more information.

Two fully funded PhD positions available

I have two fully funded PhD positions available in the context of the FAETE project.
The positions are for three years and come with no teaching duties! (There is also possibility for an extension to four years with 25% compulsory duties.) Starting date can be as early as Sept 2015, but no later than Jan 2016.

Further details and application are on Jobbnorge.
Application deadline: Aug 3, 2015

PhD positions in IR

The University of Stavanger invites applications for up to three doctorate scholarships in Information Technology at the Faculty of Science and Technology, in the Department of Electrical Engineering and Computer Science, beginning September 1, 2015.

There are 15 projects offered in total, which include two IR projects supervised by me:

#8. Living labs for information retrieval

Living labs is a new evaluation paradigm for information retrieval (IR), where the idea is to perform experiments in situ, with real users doing real tasks using real-world applications. This type of evaluation is standard practice in (large) industrial research labs, but is only now becoming available to academic researchers [1,2]. Despite recent developments, there are still numerous challenges to be overcome, including living labs architecture and design, hosting, maintenance, security, privacy, participant recruiting, and scenarios and tasks for use development. This focus of this project is on developing and employing the living labs evaluation paradigm for IR. The PhD candidate will contribute to the understanding of online evaluation and how to generalize across different use-cases.

[1] http://living-labs.net/
[2] http://www.clef-newsreel.org/

#9. Answering complex queries

Web search engines have become remarkably effective in providing appropriate answers to queries that are issued frequently. However, when it comes to complex information needs, often formulated as natural language questions, responses become much less satisfactory (e.g., “Which European universities have active Nobel laureates?”). Manual effort is often required to collect and synthesize information from multiple sources, a process that may involve a series of filtering, sorting, and aggregation steps. The goal of this project is to investigate how to improve query understanding and answer retrieval for complex queries, using massive volumes of unstructured data in combination with knowledge bases.

Details and application instructions can be found here.
Application deadline: February 24, 2015.

Important: Feel free to contact me directly for more information regarding the projects. However, applications need to be submitted on jobbnorge.no (i.e., don’t send them in email to me). Also, don’t forget to indicate which projects you are applying for, in order of preference.