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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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multiagent dynamics, with special focus on human decisions and opinion dynamics. The research will deal with both theoretical and computational aspects. The student will develop dynamical models and apply them
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modeling of magnetic materials using first-principles methods. Good knowledge of programming is required. Meritorious experience for the position is demonstrated knowledge of Git, Python, Bash and VASP. Good