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robots, tractor-implement automation, communication technologies for vehicles, navigation, guidance and planning, positioning systems, model-based control of mechatronic systems, drives and power systems
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approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with
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translational research with in-depth mechanistic studies in relevant pre-clinical GI cancer models and collaborate across scientific disciplines in two leading centers for medical research in Germany. An
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that can host an innovative form of AI which operates in hardware. This technology, called neuromorphic computing, aims to surpass the limitations of current software-based AI models, especially in terms
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The University Medical Center Göttingen (UMG) unites the Medical Faculty of the Georg-August University and the University Hospital in an integration model. With around 9,700 employees, the UMG and
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addresses these challenges in an interdisciplinary approach of A) polysaccharide chemistry, B) analytics, C) modelling, and D) bio engineering applications. Early career researchers with backgrounds in (food
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the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have
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teaching at the Chair, in particular with a focus on the planning and design of railroad systems application and continued development of digital planning methods such as Building Information Modeling
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conferences Requirements: a university degree in the field of computer science, data science, computational modeling or related subjects in combination with civil engineering, transport engineering a strong
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to): Transparency and contestability in AI Accountability in algorithmic infrastructures Technical mechanisms for evaluating and auditing AI systems Governance of open-source and general-purpose AI models Data rights