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Field
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Information Eligibility criteria Applicants must hold a PhD in graph theory and algorithms. A strong background in logic, graph decompositions, parameterized complexity, graph minor theory, and the theory
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parameters from parasite genetic data; cf., viral genomic epidemiology, where bifurcating trees capture the ancestry of DNA sequences, and human population genetics, where the ancestral recombination graph
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performance. Minimum Qualifications Required PhD or equivalent in computer science, computational biology, biomedical engineering, or a related field by the appointment start date Expertise and a demonstrated
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summarizing results, trends, and interpretation. Prepare visuals (graphs, micrographs, charts) for internal meetings and publications. 6. Collaboration and interdisciplinary communication Work in an
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, higher-order network methods and large-scale language-model training on a knowledge graph of scientific publications, patents and related innovation data. The appointed researcher will lead DII's
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures
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extracting data using advanced Natural Language Processing techniques, a knowledge graph of the Romanian labor market will be created. Through an Agent-based Modeling approach the dynamics of the labor market
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and motivated PhD student to contribute to the development of the next generation of DNA computers, capable of processing large molecular databases. The project will combine concepts from molecular
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modeling (in particular coastal research and climate research) are potentially of interest. Your profile You should have a master's degree and PhD degree in computational engineering, applied mathematics
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reputable scientific journals and present at relevant conferences to contribute to the academic and professional discourse in their respective field. Supervising PhD Students: Collaborate with and provide