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Field
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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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evaluate feature engineering and data representation strategies for heterogeneous datasets obtained from material synthesis, characterization, and functional testing. Apply uncertainty-aware modeling, active
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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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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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representations from massive amounts of raw data, typically using large-scale models that incorporate only minimal prior domain knowledge. Such representations can support a wide range of downstream tasks. However
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experimental topics in small subgroups. Teamwork is a key factor to our group’s success. Together we assembled a unique skill set and knowledge base in quantum information, quantum computation, quantum
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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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. 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
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at the national level. Through a combination of extant personal oral stories and archival sources, together with new digital humanities representations of data about infection and vaccination rates, this research
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or research centers in the field of transport and energy, contributes significantly to the advancement of knowledge on these critical issues, both for the climate and the environment. To respond