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12 février 2021

Research Associate (Postdoc) in 3D computer vision

Catégorie : Post-doctorant

SnTis a leadinginternational research and innovation centrein 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!

Your Role

We offer an attractive Research Associate (Postdoctoral) position in close cooperation with our industrial partner Artec3D. Artec3D is a global leader in handheld and portable 3D scanners and has been at the forefront of developing innovative 3D technology since 2007 (www.artec3d.com). The successful candidate will join the Computer Vision, Imaging and machine Intelligence (CVI²) research group (http://cvi2.uni.lu) headed by Prof. Djamila Aouada to conduct exciting research in the field of 3D Computer Vision. He/she will help out in shaping research directions and carry out high-impact research within the SnT and Artec3D R&D activities. The successful candidate will perform the following tasks:

  • Shaping research directions and producing results in the field of 3D Computer Vision. Topics include but are not limited to:
    • 3D shape modelling
    • 3D mesh analysis
    • 3D CAD modelling
    • 3D reverse engineering
    • Geometric deep learning
  • Disseminating results through scientific publications
  • Coordinating research projects and delivering outputs
  • Participating in writing proposals
  • Participating to the teaching activities
  • Providing support in setting up and running experiments
  • Implementing real-time solutions
  • Providing guidance to PhD and MSc students
  • Organizing relevant workshops and demonstrations
Your Profile
  • A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field
  • Competitive research record in Computer Vision, preferably with publications at top-tier CV/ML conferences/journals (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, TPAMI, TNNLS, etc.)
  • Strong development skills in Python/C/C++
  • Strong mathematical background
  • Broad experience with machine learning algorithms and deep learning concepts
  • Experience with at least one of the following deep learning frameworks: TensorFlow, PyTorch, Keras
  • Experience with relevant libraries for 3D mesh and point cloud analysis
  • Previous experience in 3D Computer Vision
  • A particular interest for 3D CAD modelling
  • Commitment, team working and a critical mind
  • Fluent written and verbal communication skills in English are mandatory
In Short
  • Contract Type: Fixed Term Contract 2 Year
  • Work Hours: Full Time 40.0 Hours per Week
  • Location: Kirchberg
  • Job Reference: UOL03837


Further Information

Applications should be submitted online and include:

  • Curriculum Vitae, including your contact address, work experience, publications, ...
  • Cover letter indicating the research area of interest and your motivation
  • Contact information for 3 referees, including contact details

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 using this link. Applications by email will not be considered.

For further information, please contactDjamila.Aouada@uni.lu.

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.

Here’s what awaits you at SnT

Find out more about us!


About the University of Luxembourg

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. The University`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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