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Postdoctoral Researcher in Semantic Knowledge Engineering & Interoperability in Materials Science in
Bundesanstalt für Materialforschung und -prüfung (BAM) | Berlin, Berlin | Germany | about 2 months agotranslated into formal knowledge representations. These form the basis for the development and integration of semantic models into ontologies and knowledge graphs as a semantic layer of federated data
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ontologies. Software development experience in Java and web application development (Javascript, HTML5 etc.) highly preferred. About You The successful applicant will be able to present information on research
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fields: Agentic AI, Large Language Models, Artificial Intelligence, Biomedical Ontologies, Biomedical Knowledge Graphs, Computational Biology, Bioinformatics, Biomedical Informatics or a related field
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spectrometry-based proteomics, including data deposition and retrieval through the PRIDE (Proteomics Identifications) database, and in bioinformatic data analysis, including pathway and ontology enrichment (ORA
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and science, and the epistemological, methodological and ontological foundations of the sciences. Faculty of Science The Faculty of Science (FNWI), part of Radboud University, engages in groundbreaking
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bioinformatics tools, including specialized research databases and software (e.g., Ensembl, Fiji, NCBI, KEGG Pathway and Gene Ontology (GO) Analysis, SPSS, etc.) (0–10 points). Experience operating bioreactors and
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Job Posting Title: Post Doctoral Scholar The Opportunity Lead and contribute research on multimodal data integration, ontology and knowledge graph building for energy domain. Supervise graduate and
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-learning methods, knowledge-graph and ontology-based scientific data infrastructures, and agentic workflows for autonomous hypothesis generation, mechanistic exploration, and design of catalytic systems
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advances in AI-based platforms for rare disease diagnosis, including systems that process free-text clinical descriptions, Human Phenotype Ontology (HPO) terms, and genetic testing results to produce ranked
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for laboratory digitalization – modern programming paradigms, connection to the electronic laboratory notebook, and development of metadata formats and ontologies – through practical learning formats such as