Sort by
Refine Your Search
-
create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
-
SQL databases and file repositories. We are now taking the next strategic step: developing ontologies and a dynamic knowledge graph to semantically link our internal data systems - and connect them
-
ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph transformation, algorithm engineering. Applications of these areas to systems
-
science, computational chemistry / biochemistry, applied mathematics, or a related area. The ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph
-
mathematics, or a related area. The ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph transformation, algorithm engineering. Applications