Temporary contract 75% part time position | 36 months | Belvaux
Are you passionate about research? So are we! Come and join us
The Luxembourg Institute of Science and Technology (LIST) is a leading Research and Technology Organisation (RTO) that drives innovation for the economy and society in Luxembourg and beyond. With cutting-edge expertise in Natural, Built, Industrial environments, Space, AI, Security and defence technologies. LIST bridges scientific excellence and applied research to design solutions that address real-world challenges and create positive impact.
Do you want to know more about LIST? Check our website: https://www.list.lu/
How will you contribute?
The Post-Doc researcher will develop, implement, and apply advanced ways in inverting a radiative transfer model for forest trait and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. You will support the development of an improved forest RTM that can exploit LiDAR full-waveform data along with hyperspectral signatures. You will plan and carry out field campaigns in Austria and Luxembourg with drone, field, and laboratory measurements for validation of the model and retrieval results. The improved methods will be applied to multi- and hyperspectral satellite (Sentinel-2, PRISMA, EnMAP) data for showcasing the improved mapping and monitoring of forest traits and uncertainties.
You will be mainly in charge of:
Develop improved hybrid model inversion methods with a focus on machine learning and deep learning and spatio-temporal regularisation
Processing multi- and hyperspectral satellite and drone data
Collection of field data on relevant forest traits and laboratory analysis
Support the development of the forest radiative transfer modelling to simulate LiDAR signatures
Lead publications in peer-reviewed journals
This position is part of an international research project together with BOKU Wien and GFZ Potsdam, jointly funded by the FNR, DFG, and FWF. We seek candidates with a strong potential to excel in a collaborative and multidisciplinary environment and use their skill for the benefit of society in the long term.
Is Your profile described below? Are you our future colleague? Apply now!
Education
PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote sensing
Experience and skills
Knowledge of quantitative remote sensing methods, particularly vegetation radiative transfer models (RTMs), and RTM inversion methods (LUT and hybrid approaches)
Profound knowledge in machine learning and deep learning methods for remote sensing applications, including architectures such as CNNs, LSTMs, and Transformers, and deep generative models (e.g., VAEs, normalizing flows, diffusion models).
Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO)
Proficiency in scientific programming using Python, with experience in Matlab and/or R considered an asset.
Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Experience in the organisation of field campaigns
Solid publication record and good scientific writing skills
Language skills
Fluency in English AND , both oral and written.
Your LIST benefits
An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
An environment encouraging curiosity, innovation and entrepreneurship in all areas
Personalized learning programme to foster our staff’s soft and technical skills
Multicultural and international work environment with more than 50 nationalities represented in our workforce
Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
Gender-friendly environment with multiple actions to attract, develop and retain women in science
32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
Flexible working hours, home working policy and access to lunch vouchers
Apply online
Your application must include:
A motivation letter oriented towards the position and detailing your experience
A scientific CV with contact details
List of publications (and patents, if applicable)
Contact details of 2 references
Please apply ONLINE formally through the HR system. Applications by email will not be considered.
Application procedure and conditions
We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.
Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above.