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Project The PhD project DC7 aims to develop and apply a coupled Agent-Based Model (ABM) and couple it to the Regional Flood Model (RFM) to evaluate the effect of adaptive behaviour of small and medium-sized
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– Multiscale imaging of organ-specific inflammation” and aims to develop and apply a quantitative MRI approach, by establishing a data base of simulated and experimental MR data of tissue and single cells
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) develop participatory planning methods based on the technical outcomes from the digital twin to create future scenarios for responsible mobility that are technically well-grounded and at the same time
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relevance. Your Tasks Antibody–Drug Conjugates (ADCs) are a rapidly advancing class of cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic agents. Upon
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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utilization. We conduct research in the field of sustainable bioeconomy, focusing on the development of innovative microbial production systems based on renewable raw materials. Our goal is to establish new bio
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the MATSim agent-based transport simulation framework. The main task is to enable simulated agents to choose transportation modes, such as car, bus, bike, or walking, based on real-time feedback from
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RAICAM aims to train a cohort of 10 PhD students to work on the next generation of mobile robots for inspection and maintenance of industrial facilities. RAICAM will develop a multi-domain, multi-agent
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industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods
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to characterize network-wide interventions, like reallocating road space or travel demand management schemes. Second, to develop an MFD-based traffic simulation linked to the agent-based simulation environment