Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process
-
Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
of the adverse effects of the space environment utilizing satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate
-
on military recruitment. Candidates on non-Italian nationality are required to: - enjoy civil and political rights also in their country of origin or provenance; - meet the above requirements, if applicable
-
carriers within defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and
-
to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
-
, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
-
and explainable hybrid Artificial Intelligence, i.e., the mix of formal knowledge representation and reasoning with sub-symbolic data-driven machine learning approaches, to work on car-driver digital
-
internationally within your field of research. Dissemination of your research to the outside world through scientific publications. Your profile Applicants should hold a PhD in chemistry/physics/materials science
-
for an excellent young life science or computational researcher to become Group Leader. Fellowships are targeted towards applicants to start their first independent group within a few years of their PhD. We offer
-
patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which