Home arrow Scholarships and Job offers arrow PhD student position on Model Interpretation for Deep Neural Networks
PhD student position on Model Interpretation for Deep Neural Networks
martes, 19 mayo 2020

The Faculty of Science is seeking to fill a full-time (100%) vacancy in the Department of Computer Science

University of Antwerp – imec IDLab Research group

The Internet & Data Lab (IDLab) is an imec research group at the University of Antwerp and Ghent University. IDLab focuses its research on internet technologies and data science. IDLab is a joint research initiative between Ghent University and the University of Antwerp. Bringing together 300 internet experts, we develop technologies outperforming current solutions for communication subsystems, high speed and low power networking, distributed computing and multimedia processing, machine learning, artificial intelligence and web semantics. Within Antwerp, where you will work, the overall IDLab research areas are machine learning and wireless networking. IDLab has a unique research infrastructure used in numerous national and international collaborations.

Project: Interpretation of Learning-based Representations

Representations learned via deep neural networks (DNNs) have achieved impressive results for several automatic tasks. This has motivated the wide adoption of DNN-based methods, despite their black-box characteristics. In this project, we aim at pushing the state-of-the-art on model interpretation of DNNs, i.e. on designing algorithms capable of revealing what type of information is encoded in a learned representation.

Job description
You prepare a doctoral thesis in the field of Machine Learning.
You publish scientific articles related to the research project of the assignment.
You contribute to teaching and research in courses given at the Department of Computer Science.

Profile and requirements
You hold a master degree in Computer Science or Electrical Engineering.
You can submit outstanding academic results.
Students in the final year of their degree can also apply.
Foreign candidates are encouraged to apply.
Your academic qualities comply with the requirements stipulated in the university’s policy.
You are quality-oriented, conscientious, creative and cooperative.
You are an open-minded individual driven by critical thinking.
You are fluent in English both speaking and writing.
You have familiarity with topics of Machine Learning, Computer Vision, and Artificial Intelligence.

You have experience with frameworks for Deep Learning (Pytorch, Tensorflow).

We offer
A doctoral scholarship for a period of two years, with the possibility of renewal for a further two-year period after positive evaluation;
The start date of the scholarship will be between May 1st 2020 and October 1st 2020;
A gross monthly grant ranging from € 2.447,20 to € 2.596,27;
A dynamic and stimulating work environment.

How to apply?
Applications may only be submitted online, until the closing date February 14th, 2020 and should include a copy of your CV and a cover letter.
A pre-selection will be made from amongst the submitted applications. The remainder of the selection procedure is specific to the position and will be determined by the selection panel.
The interviews of the candidates, preselected by a selection panel, will take place between February 17th and March 1st, 2020.
More information about the online application form can be obtained from This e-mail address is being protected from spam bots, you need JavaScript enabled to view it .
For questions about the profile and the description of duties, please contact Prof. José Oramas ( email ).

The University of Antwerp is a family friendly organization, with a focus on equal opportunities and diversity. Our HR-policy for researchers was awarded by the European Commission with the quality label HR Excellence in research.

We support the Science4Refugees initiative and encourage asylum-seeking, refugee scientists and researchers to apply for a job at the University of Antwerp.

Original Post:
https://www.uantwerpen.be/en/jobs/vacancies/ap/2020bapdocproex014/