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laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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with an interest in ecological applications. Required qualifications: PhD (or equivalent) in computer science, biology, software engineering, or a related field Strong proficiency in Python, including
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-of-the-art facilities and computing infrastructure Strong support for research career development, including mentoring and international networking opportunities A commitment to diversity, equity, and
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cultures in the Age of Revolutions by analysing connections and translation networks between four geographic zones that all underwent significant political and social change in the period between 1815 and
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international research networks time spent abroad working at one or more internationally recognised research institutions. Furthermore, applicants must have an advanced command of spoken and written academic
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well as industrial stakeholders. A research culture that encourages open dialogue, innovation, and critical thinking across fields. A collegial and inclusive workplace with networking activities, knowledge sharing