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Field
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, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a development. In the frame of a
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
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Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or related discipline. * At least 1 year of experience in bioinformatics research. * Quantitative training with good understanding
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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
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PhD programme with a focus on data science and research in the structure of matter. The graduate school covers data challenges from application fields such as structural biology, particle physics
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Spintronics, Complex systems, Theoretical Mathematical Science, Big Data, Mechanobiology / Physical Biology, Bio-energy, Genetic to Physiology, Mental Health, High Performance Computation in Physics, Chemistry