Develop applications and indicators using satellite and other remote sensing data, applying a combination of image processing, machine learning, deep learning. Process data using cloud infrastructure. Apply computer vision and machine learning techniques to satellite imagery to deduce characteristics of interest. Develop tools to assess algorithm accuracy. Contribute to the analysis and deployment of the derived information to create business-friendly and ready-to-use data and platforms. Contribute to team efforts and project definition.
There is some flexibility on exact tasks, so please get in touch if you want to discuss.
PhD in Computer Science, Computer Engineering, Physics, Geoinformatics or similar relevant field. Master’s degree accepted with demonstrable work/project experience.
Demonstrable excellence in Machine Learning, Computer Vision, Big Data (shown in PhD thesis, open-source contribution, work experience, etc). Developer profiles also considered: software development experience for developer profiles. Excellent Python and C/C++ programming skills including debugging, performance analysis, and test design. Proven experience with OpenCV, scikit-learn, SciPy, PySpark. Experience with visual object detection/object recognition, image segmentation, image classification, visual search.
Experience with development of customized Deep Learning networks like CNN;experience with the following frameworks: TensorFlow, Keras, PyTorch.
Experience in Google Earth Engine or similar will be useful as well as geospatial libraries,formats and APIs (e.g. GDAL, geoJSON). Familiarity with cloud systems (AWS/Google Cloud) and cloud infrastructure.
Self-drive and ability to take initiative.
Attitude for teamwork.
There is some flexibility on exact experience requirements, so please get in touch if you want to
Please apply with your CV, list of sofware developed, and cover letter by March 25 2021.
Applications will be processed as they are received.
• Full time or part-time. Contract or stage possible.
• Location: Luxembourg, in a start-up accelerator.
• Remote work possible.