Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Utrecht University
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- Nature Careers
- Technical University of Denmark
- Technical University of Munich
- Cranfield University
- DAAD
- Empa
- Forschungszentrum Jülich
- Leiden University
- Monash University
- UiT The Arctic University of Norway
- University of Exeter
- University of Luxembourg
- ;
- Aalborg Universitet
- Aalborg University
- Baylor College of Medicine
- CNRS
- 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 Southern Denmark
- University of Warwick
- University of Warwick;
- Vrije Universiteit Amsterdam (VU)
- 41 more »
- « less
-
Field
-
on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable
-
with data visualization (graphs, GIS maps, figures). Proficiency with GIS software and spatial data analysis is highly desirable. Strong writing skills, including the ability to contribute to manuscripts
-
Systems Biology is an international, enthusiastic, and collaborative team in an outstanding dynamic scientific environment. Research foci in the department are machine learning on graphs, machine learning
-
methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph
-
and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection, transaction classification, and
-
workflows, turning geodata into new answer maps. Knowledge graphs can be used to model these transformations and to link geodata sources to questions. In this project we will apply symbolic and sub-symbolic
-
) have some exposure to (hyper)graph theory, network science, and/or reaction mechanism/CRN studies. Candidates who do not meet all of these criteria should not feel discouraged. If you are interested in
-
for graphs; 4. Practical experience in the analysis of scientific data; 5. Proficiency in programming with Python; 6. Familiarity with the drug discovery process; 7. Ability to work on interdisciplinary
-
-analytical workflows, turning geodata into new answer maps. We use knowledge graphs to model these transformations and apply AI methods to scale them across large map repositories, enabling users to explore
-
programs. Alternatively, Mathematics, Computer Science, Computer Engineering, Electrical Engineering, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent