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methods in Social Sciences, with proficiency in data analysis procedures such as visualisation, differential analysis, mixed regression models, structural equation modelling, and supervised and unsupervised
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use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across the different organelles. Another approach is to use Monte Carlo
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interests, the project can take several directions. One option is to use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across
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into the following sections: A - Algebra, Number Theory and Logic B - Analysis and Differential Equations C - Discrete Mathematics D - Geometry and Topology E - Numerical Mathematics and Scientific Computing F
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Engineering. Familiarity with partial differential equations (PDEs) numerical analysis and / or data science and statistics will be an advantage. Number of scholarships: One Contact person: Associate Professor
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. The specific research areas we will explore are + Adaptive scientific deep learning methods for mathematical physics problems governed by partial differential equations (domain decomposition, adaptive quadrature
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aspects include rough paths and subsequent developments for nonlinear stochastic partial differential equations. The theory of signatures and rough volatility also provides important connections to algebra