Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
for the concept of optimal transport for inverse problems. Optimal transport is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions
-
of Information Technology. We investigate and develop methods, theories, and technologies for digitalized data and the information centric society. Strong mathematical, algorithmic, and computational thinking and
-
developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
-
that are of practical interest. The postdoctoral researcher will contribute to the theoretical foundations of inverse problems involving wave phenomena, develop cutting-edge computational algorithms, and apply
-
. This position will be similar to a postdoc, but with an emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused
-
, PyTorch, Keras, scikit-learn) and strong understanding of machine learning algorithms, deep learning architectures, and statistical methods Good skills in extraction of data from structured/unstructured
-
experimental materials synthesis, characterisation or both, and optionally, with experience developing algorithms for accelerated discovery based on data collection from automated instruments. Practical
-
applications at both postdoc and doctoral levels. The projects run for 4 years, and the starting date for the positions is flexible. The duration of the doctoral positions is 4 years, but the length
-
skills in programming, signal analysis and algorithms. Excellent/good skills in spoken and written English. Advantages Ability to work independently, formulate and solve research problems, and communicate
-
. Design, test, and document computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and