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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Setup a knowledge graph in neo4J for microbiome research Integration
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and interdisciplinary data integration develop new AI-based methods, tools, scripts, ontologies and a knowledge graph based on RTG research results and relevant literature provide methodological support
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Systems Biology is an international, enthusiastic, and collaborative team in an outstanding dynamic scientific environment. Research foci in the department are machine learning on graphs, machine learning
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to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics! Job description Bacterial and viral
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Do you want to contribute to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics
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technologies, such as ontologies and semantic web standards, as well as graph data and knowledge graphs, and circular economy and DPPs is preferential. Documented experience of writing and publishing research
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with data visualization (graphs, GIS maps, figures). Proficiency with GIS software and spatial data analysis is highly desirable. Strong writing skills, including the ability to contribute to manuscripts
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in writing scientific papers based on research findings. This includes generating graphs, tables, and other visuals for internal reports, grant applications, and publications. Collaborates with other
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embedding graph-based problems, particularly those known to be challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits
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on the following tasks with either with a stronger model-development or application focus: Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable