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and glycoproteomics. Computationally, they will engage in the analysis of various ‘omics data, be involved in using and improving AI models for glycan structure prediction, and perform biosynthetic
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focus is the interplay of these factors with mitochondrial translation systems and respiratory chain complex assembly. We use the yeast Saccharomyces cerevisiae as our primary research model. In
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pollution can affect natural systems and how these effects can be minimized. The work includes design and experimental studies of simple model systems as well as more applied studies. The applicant should
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numerical models and signal processing methods to detect and understand seismic events directly from communication signals in optical fibers — paving the way for a new class of communication-based seismic
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of quantum-chemical simulations are strongly desired. The candidates experienced in software for photophysical simulations (MOMAP, FCclasses, or custom handmade codes) are prioritized. In order to communicate
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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develop and improve protein-glycan binding prediction models and use AI, data science, and bioinformatics to identify and design glycan-binding proteins with desired binding specificities. Qualifications
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patterns of genomic sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models
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epidemiology to understand RNA metabolism. Perform stochastic simulations to analyze model behaviors. Fit the model parameters to empirical RNA expression and RNA-protein binding data. Predict outcomes
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock