Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- ;
- DAAD
- Nature Careers
- Technical University of Munich
- SciLifeLab
- ; University of Bristol
- CWI
- Chalmers University of Technology
- Cranfield University
- Curtin University
- Technical University of Denmark
- University of Groningen
- University of Nottingham
- Vrije Universiteit Brussel
- ; Max Planck Institute for Psycholinguistics
- ; The University of Edinburgh
- ; University of Essex
- ; University of Nottingham
- Aalborg University
- Duke University
- Fraunhofer-Gesellschaft
- Ghent University
- Helmholtz-Zentrum Geesthacht
- Institut Pasteur
- Monash University
- NTNU - Norwegian University of Science and Technology
- Radboud University
- The Max Planck Institute for Neurobiology of Behavior – caesar •
- Umeå University
- Universiteit van Amsterdam
- University of Adelaide
- University of California Irvine
- University of Cambridge
- University of Göttingen •
- University of Minnesota
- University of Twente
- University of Tübingen
- 27 more »
- « less
-
Field
-
vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
-
on agentic approaches, where an LLM interacts with visual tools, which may themselves be neural networks. Central challenges include enabling LLMs to reason about visual structures, designing
-
simulations with deep learning neural networks and swarm robots, virtual reality experiments, animal communication research, and more. In a range of projects, we show that languages can effectively be seen as
-
key regulators of inflammation and tissue remodeling in gut and skin diseases. • Apply and refine AI/ML methods, including deep learning, neural networks, and interpretable models (e.g., SHAP, BioMapAI
-
convolutional/neural networks Experience with explainable and interpretable AI (XAI) Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University’s rules
-
network attractors, funded by The Leverhulme Trust. This is a brain inspired project in the field of Neurodynamics. Networks of oscillators are ideal candidates for modelling patterns of functional
-
methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
-
communications. Evaluation of model performance can be conducted based on the data collected through the water tank. We have the GPU machines ($14k) to develop deep neural networks for underwater communications
-
the past ten years thanks to artificial intelligence, mainly in the form of deep convolutional neural networks. In parallel, functional analysis of tissue samples via novel microscopy techniques and spatial
-
to work in. Research groups: Computational Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science