Research Associate in Efficient Deep Learning for

il y a 2 semaines


Luxembourg, Luxembourg Université du Luxembourg Temps plein

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

Your Role
:

  • Shaping research directions and producing results.

Topics include but are not limited to:

  • Deep learning models suitable for deployment on edge devices (e.g., NVIDIA Jetson, FPGA, etc.)
  • Neural Architecture Search (NAS) for mínimal deep architectural design
  • Efficient inorbit object pose estimation and tracking
  • Disseminating results through scientific publications
  • Providing guidance to PhD and MSc students
  • Providing support in setting up and running experiments in the SnT Computer Vision and the Zero-G labs
  • Participating in organizing relevant workshops and demonstrations
  • Participating to teaching activities
  • Coordinating research projects and delivering outputs
  • Working closely with project's stakeholders
  • Collaborating with industrial partners

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 toptier CV/ML conferences/journals (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, TPAMI, etc.)
  • Broad experience with machine learning algorithms and deep learning concepts
  • Highly experienced in one or more of the following topics:
  • Efficient deep learning
  • Neural Architecture Search (NAS)
  • Embedded systems
  • Jetson-Nano and/or FPGA deployment
  • Object pose estimation and tracking
  • A particular interest for efficient algorithms
  • Strong mathematical background
  • Commitment, team working and a critical mind
  • Strong development skills in Python, C and C++
  • Familiarity with deep learning frameworks such as PyTorch and TensorFlow
  • Fluent written and verbal communication skills in English are mandatory
  • Advanced scientific report writing skills

Here's what awaits you at SnT
:

-
Exciting infrastructures and unique labs. At SnT's two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
-
The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 55 industry partners
-
Be part of a multicultural family**. At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more

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