-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
-
skills. Particularly meritorious is documented expertise in: Modeling and simulation of physical systems, Deep learning with applications in robotics, in particular field robotics, and Control and motion
-
in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
-
will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
-
, Micro-C/Hi-C, BS-Seq/EM-Seq), massively parallel enhancer assays (ATAC-STARR-seq), and comparative/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle