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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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Research Institute (IRBio). THE CANDIDATES: We welcome candidates interested in evolutionary developmental biology, genomics, bioinformatics and evolutionary and population genetics. Applicants must hold
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. This project represents a frontier in ecological epigenetics, marking the first application of epigenomic editing in a wild, non-model plant species. Beyond fundamental evolutionary questions, your work will
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manufacturing techniques and combines approaches from archaeology, psychology, and cognitive science. The goal of the project is to experimentally investigate the evolutionary significance of transformative Stone
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and evolutionary processes of national and international organizations). By fostering convergence among legal, political, social, and economic sciences—and utilizing cross-cutting qualitative
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to translate fundamental discoveries into sustainable agricultural applications and to enhance the climate resilience of crops. This PhD position will be embedded in the Bioinformatics and Evolutionary Genomics
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ecological changes might drive evolutionary processes, how large ecological systems adapt or not to rapid changes, what are the neural mechanisms underlying simple to complex behaviours, how do large animal
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statistical aspects Experience in next-generation DNA sequence analysis, preferably including long-read ONT data An interest in linking molecular mechanisms to evolutionary and ecological concepts The capacity
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to translate fundamental discoveries into sustainable agricultural applications and to enhance the climate resilience of crops. This PhD position will be embedded in the Bioinformatics and Evolutionary Genomics