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Field
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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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us The High-Energy part of the Theoretical Subatomic Physics group performs research into elementary particle physics from model building and Dark Matter to formal Quantum Field Theory
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compounds in complex matrices using advanced analytical techniques (e.g., mass spectrometry), as well as in assessing protein functionality (spectroscopic methods, rheology) and flavor attributes. Ability
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. The workplace The position is located at the Laboratory of Organic Electronics (LOE ), specifically within the Theory and Modelling for Organic Electronics unit in the group led by Associate Professor Glib
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model building and Dark Matter to formal Quantum Field Theory. Organizationally we are part of the division of Subatomic, High-Energy and Plasma Physics within the Department of Physics . We have a
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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to tackle the key area of critical importance to society: healthcare and biomaterials. Parlak team investigates the application of bioelectronics in medicine to meet the need for complex, dynamic environments
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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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mathematics as a major: Applied Mathematics program (bachelor's program), Mathematics and Modelling (master's program), and a Master of Science program in Engineering Mathematics. In addition to these programs
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esophageal tissue using a variety of mouse models, organoid co-cultures and spatial sequencing technologies to identify relevant cell-cell interactions. We seek a curious, highly motivated, and creative