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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit
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. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships
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perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling
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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your
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eigenvalue problems, and large-scale graph analysis). Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting
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Garcin. This comparison will be carried out from theoretical (emergence, economics, gravity, spatial interactions, graphs, urban form), methodological (robustness, error propagation, discrete choice
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled experiments is also desired, but not required
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About the Role The position is funded through the EPSRC project “Zeros, Algorithms, and Correlation for graph polynomials”. We study various combinatorially defined polynomials such as the