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and development of algorithms, methods, and theories aimed at better understanding the properties and underlying mechanisms within statistical and deep learning-based systems also in the presence
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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: You will develop software tools, algorithms, and other software components. These should be evaluated in realistic scenarios and integrated with, as well as shared within, the project team. Presentation
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is
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like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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safety. You will work on developing control algorithms all the way to performance assessment in test vehicles. The project combines theoretical aspects of control algorithms, experimental design, and
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: Experience in tree breeding, knowledge of selection algorithms/predictive models, programming skills, experience in breeding simulation, first authorship, conference presentations, strong problem-solving
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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