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approach makes it easier to identify different local optima using sampling mechanisms. In stochastic optimization, distribution estimation algorithms (EDA) are an alternative approach to traditional
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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to assess in how far vertical mixing is beneficial or detrimental for productivity under different environmental conditions (soil moisture, atmosphere) and how it might affect optimal stomatal control
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uptake, stress tolerance, and species interactions. A case in point is optimal partitioning theory (OPT), a dominant paradigm of plant resource allocation that describes the ability of plants to adjust
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to assess in how far vertical mixing is beneficial or detrimental for productivity under different environmental conditions (soil moisture, atmosphere) and how it might affect optimal stomatal control
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systems. Application areas include hot-spot cooling, energy harvesting for IoT devices, and sensorics. Main tasks: Design, synthesis, and optimization of thermoelectric thin films (n- and p-type
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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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nanophotonic sensors that disentangle multiple physical parameters from complex optical spectra. This approach raises fundamental questions on how information about parameters is optimally encoded and retrieved
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from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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are looking for someone with proven experience in semiconductor device fabrication and characterization. Responsibilities Development and optimization of silicon heterojunction solar cells at different levels