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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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composite membranes with recourse to parameters pertaining to membrane casting solutions composition, MOF structures, coating techniques and membrane casting procedure. - Modeling and optimization
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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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dedicated to developing sustainable polymers and materials via visible-light-driven processes. The core focus of this role is the design and synthesis of novel, recyclable polymeric materials using low energy
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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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) Development of deposition processes using PVD and/or electrochemical deposition (ECD) Optimization of doping and annealing processes to maximize thermoelectric performance (ZT) Structural and electrical
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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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learning methods for protein design Design of enzymes using computational models Identification and optimization of plastic-degrading enzymes Experimental expression, purification, and characterization
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yeast experience as postdoctoral researcher. Accredited experience in anaerobic process optimization and physico-chemical (microbiological) analyses. Experienced in national and international research