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Field
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computing models (non-von Neumann architectures) as a Methode for quantifying computational properties based on emergence and complex dynamics in nanomagnet systems. Nanomagnet metamaterials, Artificial Spin
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computing models (non-von Neumann architectures) as a Methode for quantifying computational properties based on emergence and complex dynamics in nanomagnet systems. Nanomagnet metamaterials, Artificial Spin
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methods to understand and model complex brain data. Key Responsibilities: For systems neuroscience focus: Perform in-vivo neural recordings in rodent models of social behavior and decision making
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(TASC) program of the ARC Industrial Transformation Research Hub for Intelligent Contaminant-Sensing in Complex Environments (IC-SensE). The TASCprogram explores consumer and workforce adoption of sensor
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21.05.2026, Academic staff The Chair of Complex Soft Matter at the TUM School of Life Sciences Weihenstephan is seeking to appoint a Postdoctoral Research Fellow (m/f/d) - Lab Automation and Data
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Demonstrable experience in qualitative research, including interviewing patients Experience of qualitative data analysis using NVivo software High level analytical capability Ability to communicate complex
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understanding of micro- and nanoplastics (MNPs) as well as risk assessment. You will gain experience engaging with complex scientific information from a variety of disciplines related to MNPS, as well as data
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Research Institute (FBRI) at Virginia Tech Carilion (VTC). About the Lab The lab integrates state-of-the-art neural recording technologies, complex cognitive tasks, and computational models to investigate
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fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can
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of Norway, focusing on the development of soft hairy surfaces for flow control and vibration-based soft robots. The overarching goal is to develop a new understanding of fluid flows coupled to complex and