Postdoc in Computer Vision for Remote Sensing

il y a 6 jours

Luxembourg Springer Nature Temps plein

**Postdoc in Computer Vision for Remote Sensing Applications**:

- Employer- Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg- Location- Luxembourg- Salary- Negotiable- Closing date- 4 Jun 2024- Discipline
Computing, Engineering, Mathematics
Job Type
Postdoctoral
Employment - Hours
Full time
Duration
Fixed term
Qualification
PhD
Sector
Academia- You need to sign in or create an account to a job.
- Job Details
- Company

**Job Details**:
**About the SnT...**

**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 University of Luxembourg seeks to hire outstanding researchers at its Interdisciplinary Centre for Security, Reliability and Trust (SnT). SnT is a recently formed centre carrying out interdisciplinary research in secure, reliable and trustworthy ICT (Information and Communication Technologies) systems and services, often in collaboration with industrial, governmental or international partners. SnT is active in several international research projects.

**Your Role...**
- Shaping research directions and producing results. Topics include but are not limited to:

- Crop classification from high resolution satellite images
- Vision Transformer (ViT) architectures on Remote Sensing imagery
- Attention mechanisms for satellite image representation learning
- Disseminating results through scientific publications
- Conducting full scale experiments, including real-time implementation, data processing, training, and validation
- Using HPC facilities for training large deep learning models
- Providing support in setting up and running experiments on large scale datasets
- 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 and Remote Sensing
- Broad experience with machine learning algorithms and deep learning concepts
- Highly experienced in one or more of the following topics:

- Transformer-based architectures for vision problems
- Training very large neural networks on HPC facilities
- Traditional machine learning techniques (e.g., Random Forests, Support Vector Machines, etc.)
- Strong mathematical background
- Commitment, team working and a critical mind
- Strong development skills in Python, C and C++
- Familiarity with one or more 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

Find out more about us

Applications, written in English should be submitted online and should include:

- Curriculum Vitae (including your contact address, work experience, publications, etc.)
- Preferably, a Github/Gitlab webpage listing completed projects in Computer Vision or Machine Learning

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.

**Company**:
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