Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- CNRS
- Forschungszentrum Jülich
- DAAD
- University of Luxembourg
- Technical University of Denmark
- Leibniz
- Linköping University
- Technical University of Munich
- University of Southern Denmark
- Utrecht University
- ; Coventry University Group
- ; Cranfield University
- ; University of Birmingham
- Cranfield University
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Harvard University
- Jagiellonian University
- Josip Juraj Strossmayer University in Osijek School of Applied Mathematics and Informatics
- Leipzig University •
- Monash University
- Roma Tre University
- The University of Queensland
- UCT Prague
- Umeå University
- University of Adelaide
- University of Antwerp
- University of Cambridge;
- VIB
- Vrije Universiteit Brussel
- WIAS Berlin
- 22 more »
- « less
-
Field
-
. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains. The position is hosted in the Leibniz Junior Research Group
-
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
-
directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
-
to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
-
to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
-
, specifically modelling the complex interrelations among infrastructure, human operators, and organizational structures using dynamic graphs, system dynamics, Agent Based Models, and discrete event simulations
-
algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
-
). Maintenance of transgenic mouse colony and embryonic fetal analysis 3). Train students and post-docs in hematopoietic research techniques 4). Prepare figures. Make charts, tables, and graphs from numeric and
-
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
-
to effectively compile linear algebra expressions when the matrix sizes are unknown at compile-time. The project aims to address the problem using e-graphs. An e-graph is a data structure commonly used in