Sort by
Refine Your Search
-
About us The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, and machine learning. Topics
-
About us The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, and machine learning. Topics
-
the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
-
Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and machine
-
work on large-scale analysis of complex traits, including Bayesian machine learning and linear mixed model approaches for trait prediction and association in high-dimensional genomic datasets, as
-
series, research seminars, and workshops. Candidates will possess a PhD (or be close to completion) in any relevant area of Management. The successful candidate will have expertise in composing large
-
Trust and is fixed-term for three years. This research position aims to develop machine learning algorithms to enable learning human ethical values from survey data. The postdoctoral researcher will
-
. Proficient in Microsoft Office Software (Microsoft Word, Excel, PowerPoint), Scientific Data Analysis and Graphing Tools and other relevant computer-based tools used in a modern research environment
-
implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
-
and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high