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Field
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of de-anonymization, including researching current de-anonymization strategies Investigate synthetic data generation methods and their utility Deploying and benchmarking the above-mentioned methods
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. Ready to be part of our team? Let’s shape the future together! About the team: Our group develops and applies quantum mechanics-based methods for the description of condensed matter systems, including
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods
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probabilistic ensemble techniques to improve uncertainty representation in climate simulations. Apply and validate Monte Carlo methods (e.g., importance sampling and other rare-event estimation methods
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application of Hamiltonian methods to gauge theories, though you will also be encouraged to develop and pursue your own research directions. Applicants should have a PhD in physics and a track record of
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, use of microscopes, data acquisition, inverse problems in imaging, optimization methods and image estimation and in particular knowledge in methods for super resolution structured illumination
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over time. This, key skills include familiarity with data management or large multi-method data sets and excellent data-analytic skills, especially those relevant to complex, large longitudinal studies
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of Information & Computer Sciences About UMass Amherst The flagship of the Commonwealth, the University of Massachusetts Amherst is a nationally ranked public land-grant research university that seeks to expand
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plasma channels, and methods for controlling injection of electrons into laser-driven plasma wakefields. This work will be undertaken within the research groups led by Prof. Simon Hooker (Oxford), in
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of phylogenomics to work with Professor Tiago Simões. The Simões lab is broadly interested in phylogenetic methods and applications, using morphological and genomic data for reconstructing evolutionary