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Applied Mathematics (TIMA)
Applied mathematics is used to study advanced methods for modeling in technology as well as natural and social sciences. The division conducts research in computational mathematics, mathematical statistics and optimization.
Mathematics and algorithms for intelligent decision-making
On the journey towards sustainability, our contribution is to develop mathematical models and solution methods for practically relevant but computationally challenging problems in scheduling and resource allocation.
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WASP Academic Doctoral Student project
Pushing the limits for large-scale discrete optimisation: New mathematics and algorithms for methods used together with Dantzig-Wolfe decomposition.
Seminars in Mathematical Statistics
The seminars are organised by the Department of Mathematics and form part of the seminar series "Seminars in Statistics and Mathematical Statistics". The topic is probability theory, random processes, statistical theory, and applied statistics.
Numerical Solutions of Time-Dependent Partial Differential Equations
Well-posedness of the governing partial differential equations lead to effective and accurate numerical methods for the analysis of physical processes in science and engineering.
Computational Cardio-Oncology
Many pediatric cancer care survivors develop serious cardiovascular complications later in life. The emerging field of computational cardio-oncology leverages advanced data methods to better predict and prevent these complications.
Optimization of Snow Removal in Cities
Snow removal in a city is a major undertaking that requires route planning and efficient driving schedules. It is a difficult and complex optimization problem and research is needed to be able to get good solutions.
Seminars in Optimization
The seminars are informal gatherings to exchange research ideas on optimization theory, algorithms, problems and applications. Organised by the Department of Mathematics.
Resource allocation and scheduling for future avionic systems
To fully utilize the potential in modern modular avionic systems, very difficult allocation and scheduling problems may have to be solved. In cooperation with Saab Aeronautics, we develop specialized solution methods for future sysems.
Modern Multivariate Statistical Analysis
Nowadays there is a great need to analyse complex high-dimensional data. Modern theories must be developed through the knowledge of the classical methods of multivariate statistics.