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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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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 hour ago
extracting mesh representations of shape and pose from image data by leveraging existing methods and/or developing novel approaches, as part of the larger goal of bringing our model(s) into active adoption
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employment with meaningful work and respectful collaboration Comprehensive onboarding and open knowledge exchange within the team Extensive training and further education programs at our UKE Academy
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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virtual representations of agricultural ecosystems. These digital twins will enhance our understanding of ecosystem functioning and carbon fluxes, supporting the design of more sustainable and resilient
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Comprehensive onboarding and open knowledge exchange within the team Extensive training and further education programs at our UKE Academy for Education and Careers Opportunities to contribute to our “UKE INside
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to potential reusers via suitable logistics chains. This includes the integration of individual stakeholder requirements and their representation by digital agents for the intelligent linking of logistics orders
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and simulation tool that will be developed in this project. Previous knowledge and experience in some of all of the following are desired and advantageous: high-level simulation tools (such as Gem5
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. This PhD project contributes to PhenoRob’s initiative to develop digital twins, i.e., high-fidelity virtual representations of agricultural ecosystems. These digital twins will enhance our understanding