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Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, Potential theory, and Dynamics Or Hershkovits Geometric Analysis Mike Hochman Dynamical systems
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computer science methods, including graph theory and deep learning, to model the evolution of molecular networks. 2. Develop and test neural architectures inspired by evolutionary optimization. 3. Identify and
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generated from density functional theory simulations, we aim to interpret complex TERS images and push the limits of nanoscale optical imaging. The student will develop and implement new theoretical
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to develop a knowledge-aware and event-centric framework for natural language understanding, in which event graphs are built as reading progresses; event representations are learned with the incorporation
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About us The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, and machine learning. Topics
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to: Investigate how logical and philosophical theories can support the structuring and modelling of knowledge in practical contexts. Participate in the development of IMF by bringing in methods from formal ontology
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Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph
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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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graph neural networks for complex sensor networks such as those involved in brain imaging Develop and test data-driven methods for image and video processing for microendoscopy. Key Duties and
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., optimization, dynamical systems, graph theory, probabilistic modeling) or adjacent fields with engineering impact. (4) Fluency in prototyping and software development (e.g., Python, C++, CUDA, or ML frameworks