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material, and produces high-quality documents. Furthermore, you have a solid understanding of numerical data and can solve numerical tasks quickly and easily. Experience in route optimization and strong
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We are seeking a highly motivated doctoral student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems
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. Background in numerical analysis and/or optimization, with interest in error estimation, convergence, and robustness to noise. Experience with geospatial data (LiDAR/photogrammetry/GIS) and handling large
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funded by the Swedish Competence Centre in Road Technology (KCV) for four years. The aim of the project is to optimize the use of recycled asphalt and marginal quality aggregates in road construction and
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consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
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, mathematical physics, mathematical statistics, number theory, numerical analysis, optimization, partial differential equations and topological data analysis. Currently, there are about 25 graduate students
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topology, algorithms and complexity, combinatorics, differential geometry and general relativity, dynamical systems, mathematical physics, mathematical statistics, number theory, numerical analysis