Location: National Observatory of Athens, Greece
Overview:
The Operational Unit BEYOND Center ( http://www.beyond-eocenter.eu/ ) for Earth Observation Research and Satellite Remote Sensing of the Institute of Astronomy and Astrophysics, Space Applications and Remote Sensing of the National Observatory of Athens, is seeking to hire a highly skilled and motivated Deep Learning Research Data Scientist to join our team and contribute to cutting-edge applied research at the intersection of Earth Observation and Artificial Intelligence. The selected candidate will play a crucial role in developing innovative approaches to address challenges related to sustainable agriculture, food security, healthy ecosystems and climate change. The ideal candidate should have a strong background in data science, machine learning, deep learning and computer vision. Experience in working with Earth Observation data is highly desired.
Responsibilities:
- Earth Observation Data Processing: Process and fuse heterogeneous earth observation and satellite remote sensing data to generate meaningful feature spaces for AI modelling and learning.
- Deep Learning Model Development: Research, design, and implement deep learning models for analyzing large-scale Earth Observation datasets. Develop and optimize deep neural networks for tasks such as image classification, object detection, semantic segmentation, and time-series analysis.
- Paper Writing: Showcase the results of the research by (co-)authoring technical reports, and research papers in highly regarded conferences and journals.
- Participation in European Projects - Contribution to proposal writing, project realisation, and deliverable preparation: Our research and technical outputs are mainly realized in the context of EU, ESA and other funding Institutions’ projects. As part of our team, you will actively participate in such projects and contribute to proposal writing for attracting new funding in collaboration with the Project Managers of the unit. Your involvement in collaborating with other institutions and organizations across Europe will foster a dynamic and collaborative research environment, driving the advancement of our mission in agro-environmental research. Your participation in projects will require the participation of the team undertaking the preparation of deliverables and reports.
- Travelling: In the context of working in research and research and innovation projects and making research publications, you will get to travel across Europe and the world to participate in plenary meetings, international conferences, and workshops to present scientific results.
Qualifications:
- Master's degree or higher in Data Science, Computer Science, Environmental Sciences, or a related field with a focus on Earth Observation data analysis, deep learning, and computer vision.
- Demonstrated experience in applying deep learning techniques, computer vision algorithms, and data analysis to complex datasets, particularly in the context of Earth Observation data.
- Proficiency in programming languages such as Python, along with experience working with deep learning frameworks (e.g., TensorFlow, PyTorch), geospatial data, and relevant libraries (e.g., GeoPandas, rasterio).
- Knowledge of remote sensing data processing techniques and familiarity with Earth Observation data formats (e.g., NetCDF, GeoTIFF) is a plus.
- Proven track record of scientific publications in relevant fields is a bonus.
- Strong problem-solving skills, analytical mindset, and the ability to work both independently and collaboratively in a research team.
- English language proficiency preferably at C2 level, both written and spoken.
Join our team to make a meaningful impact on state-of-the-art research that contributes to understanding and addressing critical agro-environmental challenges through the integration of Big Earth data and Artificial Intelligence. We offer a stimulating and collaborative work environment with opportunities for professional growth and participation in prestigious European, national and commercial projects. To learn more about our team's projects and research, visit our GitHub page: https://github.com/Agri-Hub.
We Offer: A high competitive remuneration package based on the qualifications of the candidate including all legal deductions and taxes.
Indicative start date: October 2023
Deadline for CVs: September 30th, 2023
How to apply: Interested applicants should send their CVs to This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it.. You don’t need to send a cover letter.
Operational Unit BEYOND Center of IAASARS/NOA is an equal opportunity employer