Job Summary Table of Deep Learning Research Associate for Space Applications

Job Description Summary

The University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT) is seeking a Research Associate to join their Computer Vision, Machine Intelligence and Imaging (CVI²) research group. This exciting role focuses on developing efficient deep learning models for computer vision applications in space technology.

Responsibilities

• Shape research directions and produce results in deep learning for edge devices
• Develop and implement neural architecture search (NAS) techniques
• Work on efficient in-orbit object pose estimation and tracking
• Disseminate research findings through scientific publications
• Provide guidance to PhD and MSc students
• Set up and run experiments in SnT’s Computer Vision and Zero-G labs
• Organize relevant workshops and demonstrations
• Participate in teaching activities
• Coordinate research projects and deliver outputs
• Collaborate closely with industrial partners and project stakeholders

Benefits and Perks

• 🚀 Access to cutting-edge research facilities, including the LunaLab and nanosatellite development labs
• 🌍 Join a multicultural team with over 60 nationalities represented
• 🤝 Engage in demand-driven projects through SnT’s Partnership Programme
• 🎓 Opportunities for professional development and career growth
• 🏆 Work at a top-ranked international research university

Company Overview

The University of Luxembourg is a young, dynamic institution known for its international character and interdisciplinary approach. Founded in 2003, it has quickly risen to prominence, ranked #3 worldwide for its “international outlook” by Times Higher Education. The university focuses on cutting-edge research in areas such as Computer Science, ICT Security, Materials Science, and more.

Company Culture

At SnT, you’ll be part of a vibrant, innovative community dedicated to pushing the boundaries of technology. The centre values collaboration, creativity, and excellence. Throughout the year, team-building events and networking activities foster a sense of camaraderie among colleagues from diverse backgrounds.

Career Growth Opportunities

This position offers significant potential for career advancement. With the possibility of extension up to 5 years, you’ll have ample time to develop your research portfolio, collaborate with industry partners, and contribute to groundbreaking projects in space applications and computer vision.

Diversity, Equity, Inclusion, and Belonging

The University of Luxembourg embraces inclusion and diversity as key values. They are committed to removing any discriminatory barriers related to gender or other factors in recruitment and career progression.

Equal Opportunity Statement

The University of Luxembourg is an equal opportunity employer. All qualified individuals are encouraged to apply, regardless of their background, gender, race, or nationality.

Remote Work Policy

This position is based on-site at the Kirchberg campus. However, the university provides state-of-the-art facilities and a collaborative environment to ensure a productive and engaging work experience.

Application Process

1. Prepare your application documents, including CV, contact information for 3 referees, and links to relevant projects (e.g., GitHub/GitLab)
2. Submit your application through the official HR system
3. Applications will be processed upon reception, so early application is encouraged

Application Deadline

Info not available

How to Apply

Please apply online through the official HR system. Applications sent by email will not be considered.

Social Media Links

Info not available

FAQs or Additional Information

What makes this position unique?

This Research Associate role offers a rare opportunity to work at the intersection of deep learning, computer vision, and space applications. You’ll be developing cutting-edge algorithms that could potentially be deployed on edge devices in space, contributing to the advancement of space technology and exploration.

What kind of projects will I be working on?

You’ll be involved in various projects focusing on efficient deep learning for computer vision space applications. This may include developing models for in-orbit object pose estimation and tracking, implementing neural architecture search techniques for minimal deep architectural design, and optimizing algorithms for deployment on edge devices like NVIDIA Jetson or FPGAs.

What are the research facilities like?

SnT boasts state-of-the-art facilities, including the Computer Vision Lab and the Zero-G Lab. These unique environments allow researchers to conduct full-scale experiments, including real-time implementation, data acquisition, training, and validation for space-related applications.

Is there opportunity for collaboration with industry partners?

Absolutely! SnT has a strong Partnership Programme with over 55 industry partners. This position involves close collaboration with industrial stakeholders, giving you the chance to work on real-world problems and see your research applied in practical settings.

What are the qualifications required for this position?

The ideal candidate should have: – A PhD in Electrical Engineering, Computer Science, Applied Mathematics, or a related field – A strong research record in Computer Vision, with publications in top-tier conferences/journals – Extensive experience with machine learning algorithms and deep learning concepts – Expertise in topics such as efficient deep learning, neural architecture search, embedded systems, and object pose estimation – Strong development skills in Python, C, and C++ – Familiarity with deep learning frameworks like PyTorch and TensorFlow – Excellent communication skills in English

If you’re passionate about pushing the boundaries of deep learning in space applications and have the skills to match, we encourage you to apply for this exciting opportunity at the University of Luxembourg’s SnT!

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