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evolution by analysing it as an algorithm? And extend the mathematics of theoretical computer science to create new theories of biological & cultural evolution in cancer, metascience & other domains? Join us
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adjacency matrix of a graph 𝒢, where the edges represent the coefficients a_{ij} for i ≠ j, and the nodes represent the coefficients a_{ii}. We then train a Graph Neural Network (GNN) to predict without
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related to staff position within a Research Infrastructure? No Offer Description Are you looking for a PhD position and interested in algorithm development for genomics? Do you want to innovate methods
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causal knowledge graph, prepare an operational algorithmic platform, answer and explain complex questions about the known and possibly unknown phenomena, address ethical and inequality protective issues
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, random graph theory and (general) resource allocation algorithms/scheduling. Strong independency in analytical thinking, and intrinsic drive to deep thinking and complex problem solving. Enthusiasm
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causal knowledge graph, prepare an operational algorithmic platform, answer and explain complex questions about the known and possibly unknown phenomena, address ethical and inequality protective issues
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methods and graph neural networks; developing open-access software tools (such as R and Python packages or C++ libraries) for applying the newly developed algorithms/models and techniques to real-world
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intermittently-available), with applications to distributed autonomous systems. In particular, statistically robust, probabilistic machine learning algorithms will be explored for time-varying graphs, which
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systems. In particular, statistically robust, probabilistic machine learning algorithms will be explored for time-varying graphs, which naturally arises in mobile autonomous systems, tackling challenges
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algebra, high-performance computing) and computer science (graph algorithms) and with a strong interest in engineering applications. This project will be supervised by prof. Stefan Vandewalle (Numerical