SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent.
We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place!
The Parallel computing and Optimisation Group (PCOG) is led by Prof. Pascal Bouvry and Dr. Grégoire Danoy as deputy head. PCOG conducts research on parallel computing and optimization techniques, in particular how different species may co-evolve taking local decisions while ensuring global objectives, to tackle large and difficult problems. The main application domains are security, trust and reliability; reliable scheduling and routing on new generations of networks; sustainable development and systems biomedicine; Unmanned autonomous vehicles (UAV), Smart Cities. Detailed information about the group is available at http://pcog.uni.lu/
This is a fully funded position for 3 years (extendable to an additional 4th year) in the ADARS (Automating the Design of Autonomous Robot Swarms) financed by the FNR.
The ADARS project aims to propose a unique approach to automatically generate behaviours for distributed aerospace and space systems (DASS) thanks to a cross-fertilisation between multi-objective optimisation and machine learning techniques. ADARS will demonstrate through specifically designed software simulations and real field tests with multi-rotor drones, that state-of-the-art results can be obtained on two challenging DASS applications: swarm formation for a counter UAV system and swarm formation of small satellites for asteroid observation.
The successful candidate will work under the academic supervision of Dr. Grégoire Danoy (University of Luxembourg) and join a strong and motivated research team of SnT.
The position holder will be required to perform the following tasks:
Qualification: The candidate should possess an M.Sc./M.Eng. Degree in any discipline relevant to this area of research (e.g., computer science, applied mathematics or a related field),
Experience: The candidate should have some knowledge and experience in some of the following topics:
Language Skills: Fluent written and verbal communication skills in English are mandatory.
But wait, there’s more!
Students can take advantage of several opportunities for growth and career development, from free language classes to career resources and extracurricular activities.
Application should include:
All qualified individuals are encouraged to apply.
Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered.
The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.
The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character. It fosters the cross-fertilisation of research and teaching, is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. It`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society.
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|Titel||PhD Position in Automated Design of Swarms of Distributed Aerospace and Space systems|
|Employer||University of Luxembourg|
|Job location||6, rue Richard Coudenhove-Kalergi, L-1359 Luxembourg|
|Publicerad||december 1, 2020|
|Ämnen||Algoritmer,   Rymdteknik,   Artificiell intelligens,   Distribuerad databehandling,   Kontrollsystemteknik,   Maskininlärning,   Systemteknik  |