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application! This position is in a lab with an interest in many aspects of theoretical ecology (coexistence, niche theory, ecological networks, metacommunities, eco-evolutionary dynamics, and more), where you
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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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general problem for all life that underwent endosymbiosis at some time during their evolutionary history. Depending on the applicant’s interests, the project can take several directions. One option is to
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, within the subject of the position, e.g. within genetics, genomics, evolutionary biology using bioinformatical approaches or within molecular biology addressing evolutionary questions. While there are no
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-organelle coordination. Besides plant cells, such coordination is a general problem for all life that underwent endosymbiosis at some time during their evolutionary history. Depending on the applicant’s
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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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your application! We are looking for a PhD student in evolutionary genetics interested in contributing to a better understanding of the mechanisms that shape mutation rates. Your work assignments
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to study the evolutionary history of molt phenology across related species of grouse. The project will also use functional genomics to study the regulatory mechanisms of molt phenology in grouse
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, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain
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consequences of higher host specialisation in the tropics – the role of ecological and evolutionary processes, and of data bias), and the successful applicant will work in the Evonets lab (evonetslab.github.io