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The Max Planck Institute for Neurobiology of Behavior – caesar • | Bonn, Nordrhein Westfalen | Germany | 3 days ago
Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content Join our fully-funded international PhD programme in neuroscience! The International Max Planck
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positions) : the deadline depends on the respective advertised open positions. Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No
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of texts; or the question of the co-validity of multiple interpretations. the standards and types of argumentation accepted or expected in different kinds of commentary, e.g. the role of appeals to authority
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genres, e.g. the role of preliminary questions in establishing the meaning of texts; or the question of the co-validity of multiple interpretations. the standards and types of argumentation accepted
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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balance between accuracy and computational efficiency, while also enabling the modelling of aging effects in polymer systems. Objectives: The primary objective of this project is to develop an advanced MACE
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations
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): Automated bidding strategies for participating in multiple markets (hydrogen, electricity) over different time scales, such as short-term forward markets and spot markets (operating in real-time). This can be
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– Hereby we offer a PhD Thesis focusing on the topic of Transport Modelling for Sustainable Mobility . Our main goal is to further develop and apply the agent-based simulation framework MATSim. The existing
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the value of the green transition. The project will involve a multi-stakeholder innovation process, utilizing a framework of multiple-loop learning to encourage farmers to reflect on their relationship with