Postdoctoral Researcher in Explainable AI
Vrije Universiteit Brussel Department of Electronics and Informatics


Despite the success of deep learning in various tasks, its limiting factor is that its understanding remains underdeveloped, which in turn translates into a lack of principled methods to design efficient deep-neural-network architectures. This postdoctoral opening focuses on research around explainable artificial intelligence (XAI). Specifically, the research revolves around new designs and theory for interpretable deep neural networks, which promote the underlying structure in the data (expressed, for example, by graphs, sparsity or low-rank properties), and are supported by guarantees and posthoc analysis. The research covers areas including (but not limited to) geometric deep learning, deep unfolding, and automatic machine learning.

The position is within the Department of Electronics and Informatics ( at Vrije Universiteit Brussel, Belgium, which specializes on signal processing, machine learning, and information theory for big data acquisition, mining, processing and analysis. The team is affiliated with imec, an international R&D and innovation hub in nanoelectronics and digital technologies (

The successful candidate will complement the existing team of several researchers working on fundamental and industrial research projects. The key responsibilities are:

Contributing to the design and development of novel algorithms and analysis methods for explainable deep learning with application in visual computing and/or big data;
Contributing to the design and development of experiments for the validation and fine-tuning of the algorithms;
Contributing to the preparation of scientific publications and patents;
Guidance and supervision of junior researchers.
We are especially interested in candidates with the following profile:

A PhD degree focusing on artificial intelligence, machine learning, signal processing, computer vision, or related;
An excellent academic record with publications in top-tier scientific journals and conference proceedings;
Fluency in statistical learning and representation learning, for example deep neural networks, matrix factorization, generative models, reinforcement learning;
Fluency in state-of-the-art machine learning tools (Tensorflow, PyTorch, Caffe);
Fluency in English and excellent scientific writing skills;
Experience with high-dimensional data, for example image/video data, IoT data, networked data.
We are offering a two-year position, extendable further subject to performance, including a competitive salary and benefits. The successful candidate will work in an international scientific environment driven by excellence in fundamental research. The position provides a great opportunity to the researcher to work in close collaboration with established companies.

Interested candidates can send: (i) a detailed curriculum vitae; (ii) a motivation letter related to the position's profile; (iii) electronic copies of three key scientific publications; and (iv) the names of two potential referees by September 10, 2019 to the following contact person:

Prof. Dr. Nikolaos Deligiannis

Vrije Universiteit Brussel – imec

Pleinlaan 2, Brussels 1050, Belgium
Tel.: +32 2 629 1683


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