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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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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
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reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be
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. Eran Elhaik to design machine-learning models that unlock the potential of genomics for forensic investigations and historical reconstructions. Work duties We aim to develop machine learning methods
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 1st September, or as