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rules in networks of complex spiking neuron models in the application field of geolocalization: Building up simulation model for networks of complex neurons with topologies close to neuroscience models
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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Your Job: Healthy brain function relies on dynamic changes at the synapse. The relevant synaptic turnover and plasticity processes span spatial scales from the molecular up to the network level, and
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simulation of technical systems Interest in practical work with catalysts, laboratory setups and pilot-scale plants Ability to analyse complex interrelationships and work methodically Good written and spoken
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chemical and/or biological laboratories Ability to work independently as well as collaboratively in an interdisciplinary and international research environment Based on the complexity of the project
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laboratories Based on the complexity of the project, motivation to learn new skills to expand scientific knowledge High degree of analytical working style Excellent communication skills and ability to work in an
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addition, the dynamics and transport processes across the UTLS adds complexity to unveil the role of UTLS aerosols in cirrus formation and the life cycle of cirrus. Therefore, it is crucial to measure
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to gain insights into complex systems and inform decision-making Design and evaluate scenarios that focus on energy systems and structural change, assessing their potential impact Develop and evaluate
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mineral surfaces Parameterize, set up, and validate molecular-scale models of complex soil-relevant systems Quantify structural, dynamical, and energetic properties governing water retention and soil
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. The relevant synaptic turnover and plasticity processes span spatial scales from the molecular up to the network level, and temporal scales from seconds to hours and beyond. The aim of this PhD project is to