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education at the department occurs in an international environment and is focused on animal biology. Outstanding and high impact research is conducted in a variety of fields, including evolutionary biology
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Description: This project is in the research field of applied evolutionary ecology, aiming at understanding ecological and evolutionary processes that may be relevant for the development of sustainable plant
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model species, the PhD student selected for this project will investigate unanswered questions on how complex
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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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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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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corresponding knowledge in another way. A successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms
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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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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