Doctoraatsbursaal -  Department Telecommunications and Information Processing

Doctoraatsbursaal - Department Telecommunications and Information Processing

Belgium 01 Sep 2021
Ghent University

Ghent University

State University, Browse similar opportunities


State University
Host Country
01 Sep 2021
Study level
Opportunity type
Opportunity funding
Full funding
Eligible Countries
This opportunity is destined for all countries
Eligible Region
All Regions

Uiterste inschrijvingsdatum: Sep 01, 2021 00:00

Vakgroep/directie/dienst: TW07 - Vakgroep Telecommunicatie en Informatieverwerking

Type contract: Contract van bepaalde duur

Diploma: Master of Science in Engineering, Applied Sciences, Physics, Computer Science or Mathematics

Bezettingsgraad: 100%

Vacature type: Overig academisch personeel


The research group for Artificial Intelligence and Sparse Modelling (GAIM) is part of the Department Telecommunications and Information Processing (TELIN) at the Faculty of Engineering and Architecture at Ghent University. GAIM’s research is at the intersection of machine learning, signal processing and information theory. We pursue the development and integration of innovative algorithms for representation learning, deep learning and sparse coding, pattern recognition and classification, information recovery from partial, corrupted and high-dimensional data as well as inference algorithms for solving generic problems described by probabilistic graphical models and reasoning under uncertainty. The application areas of our research include machine vision, biomedical processing, remote sensing and art investigation.

The Royal Military Academy of Belgium (RMA) is a military institution of university education responsible for the basic academic, military and physical training of future officers, and for the continued advanced training of officers during their active career in the Defense department ( RMA is also conducting scientific research at university level for projects funded by Defense or by external sources.

Job description

The project “Automatic, small-scale sea-floor characterization from high-resolution sonar data, (A4S)” consists in developing an AI-based model to extract information from high-resolution sonar data in order to characterise environmental parameters in (near)real-time. From that information, Additional Military Layers* are to be created to enhance environmental awareness for mine-search and maritime surveying applications.

The successful candidate will have, under the supervision of the project (co-)directors and (co-)supervisors, to devise the necessary algorithms, implement, evaluate their performance and validate them. The candidate is also expected to publish the relevant results in the scientific literature while taking the industrial valorisation of these results into account.

The successful candidate will be integrated in the “Image Processing” research cell of RMA and in the research Group for Artificial Intelligence and Sparse Modeling (GAIM) at the Department Telecommunications and Information Processing of UGent.

The successful candidate will be supervised by Prof. Xavier Neyt from RMA and Prof. Pizurica from UGent; and assisted by Dr Ir Lopera, from the “Image Processing” research unit.

More information at:

*AML are a range of digital geospatial products. Endorsed by NATO and coordinated by the UKHO, AML provide tactical
advantage in military and humanitarian operations by using geospatial intelligence.


Skills/Qualifications Required

The applicant shall have:

Personal skills

Other skills

Specific requirements:

Additional information


Extra-legal benefits


You will be working in a military environment. For this reason, you will be subject to a security screening.
Please add to your job application a duly completed copy of the following security screening document that you can download from the web-site of RMA (currently available only in Dutch or French):

Applicants shall send :

Please mention clearly the reference of the project “A4S”, and send your application to Prof. Xavier Neyt ( ), Prof. Aleksandra Pizurica (, to Dr Olga Lopera ( and to the service RSWO (

Application deadline: June 4th, 2021

A first pre-selection will be conducted based on the received documents. Preselected applicants meeting the requirements will be invited to a face-to-face interview (optional online; depending on the COVID-19 situation) at the Royal Military Academy, rue Hobbema 8, 1000 Brussels. The date and time of the interview will be communicated to the preselected candidates.

Other organizations

Choose your study destination

Choose the country you wish to travel to study for free, work or volunteer

Please find also