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design. The programme aims to promote social science with the city. Whether working with activists or policymakers, medical doctors or social workers, the goal is to learn from local partners and work
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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mechanisms, Sensors and instrumentation, Data analytics, machine learning, or AI, Digital twins or physics-based modeling, wide-bandgap semiconductor technologies. Excellent written and spoken English
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is decentralized or only partially observable? Depending on the research direction, you may employ techniques from mathematical modelling, machine learning, uncertainty quantification, distributed
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strong affinity with the study of socio-economic and ethnic inequality; has experience with advanced quantitative methods (or is motivated to learn); ideally has experience with large-scale, complex data
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mental models, cognitive maps, and cognitive graphs. These approaches have provided important insights into how people perceive locations, learn route layouts, and understand spatial relations. However
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-sector partners; able to work both independently and collaboratively; eager to learn new methods and broaden your research expertise; motivated to publish in leading international scientific journals and
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the institute and the academic community, a dedicated and passionate atmosphere prevails. The themes of Health and Wellbeing, Social-Cognitive-Affective Decision Making, Development and Learning, and Advanced
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are the same. You will have the opportunity to share your ideas, develop yourself professionally, and acquire new skills. Innovation and collaboration are at the heart of our work. You will be part of
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in laboratory work and materials characterization techniques (e.g. SEM, ICP-MS) Basic knowledge of thermodynamic modelling or willingness to learn tools such as FACTSage Analytical mindset with strong