Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
difference. Make something out of it! In our video you will find information about our student assistants and their work. What you will do Driving innovative AI research through the development and
-
aims to develop responsible transport appraisal methods that consider multiple performance metrics simultaneously, with a special emphasis on fairness to weigh different circumstances, constraints, and
-
diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry
-
architectures and orchestration and documentation experiments Analysis and preprocessing of different data types (time series, graphs, images, matrices) Processing and visualization of huge amounts of data
-
architectures Analysis and preprocessing of different data types (texts, images, time series, graphs, etc.) Review latest literature and data Orchestration and documentation of deep learning experiments
-
-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
-
data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
-
technology. ▪ Close connection to the activities of the Munich Quantum Valley with its main goal to build a quantum computer based on different platforms, to develop suitable algorithms and applications, and
-
position / internship in the field of dependable person detection. Your task is to investigate, how reliably different object detection algorithms can recognize and locate persons. This will include 3D
-
this, these simulations need to be massively parallelized. The objective of this thesis is to implement and evaluate different contingency parallelization approaches using our group's computational infrastructure