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focuses on innovative multidisciplinary research and educational programmes that are constantly renewed in response to issues in society. Our faculty is large enough to make a difference nationally and
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educational programmes that are constantly renewed in response to issues in society. Our faculty is large enough to make a difference nationally and internationally, yet small enough to offer personalised
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the Reinforcement Learning Lab for Sustainable Energy, researchers from academia and industry develop, implement and evaluate new deep reinforcement learning methodology to solve sustainable energy challenges
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, and the meaning attached to them in scholarly work and in the eyes of society. We encourage candidates to develop their own focus within the project. However, we would be particularly interested in
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students and staff to feel valued and respected and to develop their full potential. Diversity in experiences and perspectives enriches our teaching and strengthens our research. High quality teaching and
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and interdisciplinary research field. You will assist with student supervision and teaching and complete a PhD thesis in four years. Requirements Specific Requirements Selection Criteria Master degree
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supervision and teaching and complete a PhD thesis in four years. Selection Criteria Master degree or similar in biodiversity-relevant field, such as ecology, communication research, urban planning
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University. Specifically, we invite applicants to develop an innovative PhD proposal on empirical and normative issues around the ‘Climate Migration’ Dilemma (see next section). The PhD project will be
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the ongoing dialogue surrounding sustainable infrastructure development. The candidate will develop methodologies capable of modeling the trajectory of global infrastructure development, guiding it toward a
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at workshops and conferences; Participation in the training programme of the Graduate School; Co-organizing workshops and conferences; Limited teaching duties in the second and third years. Requirements for PhD