Sort by
Refine Your Search
-
of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
-
learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
-
– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
-
, Computer Science, Artificial Intelligence, Theoretical Computer Science, Computer Engineering, Practical Computer Science Description Description The CISPA Helmholtz Center for Information Security is
-
dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
-
biology, cell biology, biochemistry, and plant-microbe interaction research come together to advance sustainable agriculture and reduce reliance on pesticides and mineral fertilizers. Further information
-
Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German
-
“DiamondNanoNMR” we are looking for ambitious PhD students (75%, TV-L E13, limited to 3 years). Our mission is to apply quantum information concepts to nanoscale sensing. This emerging technology stands
-
considers the transport of suspended matter (tracers); calibrating and validating the model against long-term data on hydraulic conductivity, water temperature, and dissolved oxygen from several rivers
-
available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling