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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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their glial niche. Genetically encoded, fluorescent metabolite sensors will be used to study the underlying metabolite dynamics. The work will also incorporate various molecular biology techniques, as
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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- looking. Sensor technology plays a key role in this transformation, enabling real-time monitoring, automation, and intelligent decision-making. Despite these needs, many water treatment processes still rely
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meteorological stations and occasionally supplemented by opportunistic sensors. The integration of diverse opportunistic sensor data sources [4], such as private weather stations, further broadens the capability
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate
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, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
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living allowance, a mobility allowance and a family allowance (if eligible)) starting November 1, 2025. Research areas: DC7: Programming models and high-level compilation for near-sensor dataflow execution