Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
-
machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
-
writing skills. o Proactive mindset and ability to work in a multidisciplinary and collaborative environment. o Adaptability and openness to learn new tools and methods. Language skills
-
approach for OFR, building further on existing methods; (2) quantify the value of OFR in Luxembourg ; (3) quantify the impact of forest disturbances on the OFR supply and value; (4) estimate the supply and
-
letter Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. All
-
methods and solutions and in architectures and systems that support the development of such systems Publish research results and present them at international conferences Contribute to reports and research
-
into this material and support tailoring its properties. For this, you will: Contribute to method development for ultra-fast MLIPs (Xie et al., npj Comput. Mater., 2023) Develop realistic MD simulation protocols
-
) - Three-dimensional conformally flat Lorentzian manifolds through experimentation (Karin Melnick) - Representation-theoretic methods in algebraic geometry (Karin Melnick & Pieter Belmans) - Computational