Sort by
Refine Your Search
-
Category
-
Country
-
Field
-
Research Project“ Transforming Cardiac Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts
-
below? Are you our future colleague? Apply now! Experience and skills · You have a strong interest in terrestrial ecosystems modelling, vegetation demography, plant physiology, and climate change
-
a powerful way for assessing forest stress and disturbances over large areas and to monitor forest vitality over time. This research uses remote sensing technologies together with physical models and
-
susceptible to SM, VWC, and atmospheric delay. As a result, the objective of this PhD project is to develop models able to fuse backscattering and phase information to estimate SM and VWC more accurately. The
-
: 01.10.2025 Application deadline: 03.09.2025 Tasks Execution of experimental work in a mouse model of cortical multiple sclerosis Application of in vivo imaging and quantitative analysis methods Investigation
-
mechanisms. The overall goal of the research project is to develop process understanding and parametrizations that lead to improved, energetically consistent, climate models. Close collaboration with the other
-
diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
-
particles - in promoting inflammation and fibrosis, and work to identify specific biomarkers of exposure and associated risks in human and mouse models. Develop and evaluate therapeutic strategies to target
-
interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
-
analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image