Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Nature Careers
- Technical University of Denmark
- Technical University of Munich
- Utrecht University
- CNRS
- Cranfield University
- DAAD
- Empa
- Forschungszentrum Jülich
- Leiden University
- Monash University
- UiT The Arctic University of Norway
- University of Exeter
- University of Luxembourg
- University of Southern Denmark
- ;
- Aalborg University
- Baylor College of Medicine
- Computer Vision Center (CVC)
- DIFFER
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); yesterday published
- Imperial College London;
- Institute of Image-Guided Surgery of Strasbourg
- Jagiellonian University
- Leibniz
- Leiden University; Leiden
- Leipzig University •
- Linkopings universitet
- Luxembourg Institute of Science and Technology
- Massachusetts Institute of Technology (MIT)
- Max Planck Institute of Biochemistry, Martinsried
- NTNU - Norwegian University of Science and Technology
- New York University
- The University of Edinburgh;
- The University of Queensland
- Umeå University
- Umeå universitet
- Universitat Politècnica de València
- University College Dublin
- University of Adelaide
- University of Birmingham;
- University of Cambridge;
- University of North Texas at Dallas
- University of Warwick
- University of Warwick;
- Vrije Universiteit Amsterdam (VU)
- 40 more »
- « less
-
Field
-
, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and
-
shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational
-
one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
-
graphs for heterogeneous pavement engineering knowledge aiming to speed up the learning cycle and support innovation and asset management. Job description The increasing accessibility of data in
-
Apply and develop advanced multimodal data tools and knowledge graphs for heterogeneous pavement engineering knowledge aiming to speed up the learning cycle and support innovation and asset
-
research documentation, including ethics and funding applications Assist with routine team administration Assist with preparing reports, graphs, figures and presentations on research outcomes at different
-
shifts in cell state and cell fate. Integrate spatial transcriptomics data to anchor these predictions in tissue context. Develop machine learning methods (e.g. graph neural networks, variational
-
XAI methods, e.g. counterfactuals in reasoning and knowledge graphs (KGs) based on domain expertise, to strengthen inferences drawn from data, and to reduce complexity of learning – by factual reasoning
-
biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
-
: algorithmics, graph transformation and algorithm engineering. Exposure to systems chemistry or systems biology is an asset but not a must. Proven competences in programming and ease with formal thinking are a