Research Associate in Efficient Deep Learning for

Il y a 7 mois


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 in-orbit 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 top-tier 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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