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of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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The Bernhard Nocht Institute for Tropical Medicine (BNITM, https://www.bnitm.de/en ) is the largest Research Institute for Tropical Medicine in Germany with approximately 420 employees. It is the
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, AAAI). Demonstrated expertise in at least two of the following areas: semantic parsing or structured NLP knowledge representation, reasoning graphs, or GNNs natural language generation, explainability
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 5 hours ago
, or knowledge representation systems. Interest in human–AI collaboration and socio-technical system design. Experience contributing to open-source projects. If you fulfill all the requirements, you may be
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research stays at partner institutions representation of the project at national and international workshops and conferences, as well as contribution to scientific publications Requirements: completed
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) If the legal requirements for civil servant status are not met, employment may be possible under a private employment contract. The professorship involves representation of the designated field in both research
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 2 months ago
field of conceptual development for the automated synthesis of auditory and textual explanations, implementation and evaluation of the overall system Ontology development and knowledge representation
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LMU Munich. The group is located within the Institute of Clinical Neuroimmunology (https://www.neuroimmunology-munich.de/ ). The professorship of Systems Neuroimmunology is part of the Cluster
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. Empirical data will be used to support the development and parameterization of the agent-based model, enabling a more realistic representation of IAM travel behavior and its interaction with existing