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 successful candidate will join the LEGATO team led by Prof. Stephane Bordas by contributing to the Data-Driven Approach for Urban Wind Energy Harvesting - DATA4WIND project granted by Luxembourg National Research Fund (FNR).
It is expected for the candidate to perform following tasks :
Performing systematic literature review on possible reduced modelling techniques (including meta-models and artificial neural networks) with direct application in wind engineering
Implementing different model reduction approaches in the Reduced Order Modelling tool
Testing developed tool for wind flow over urban location based on the experimental and computational fluid dynamics data sets
Exploring the use of a developed reduced modelling tool for urban comfort studies
Disseminating results through scientific publications
Preparing project deliverables and reports
A PhD degree in Computer Science, Engineering or a related field
Competitive research record in one of the following areas : Reduced Order Modelling (including meta-models and artificial neural networks) and / or Computational Fluid Dynamics
Relevant knowledge of Wind Engineering will be treated as a benefit
Strong development skills in Matlab, Python and / or C++
Documented research experience in a number of the aforementioned topics
Commitment, team working and a critical mind
Fluent written and verbal communication skills in English are mandatory
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