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interactive prototypes for scenario testing and stakeholder engagement. Collaborate closely with the PhD researcher to connect environmental data analysis with computational design innovation. Participate in
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our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. PhD Researcher: AI-Enhanced Adaptive Design for Dynamic
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An environment where we care about your career development. For example, receiving mentoring, training on large-scale computing, or possibilities of mentoring PhD/MSc students and teaching, if that is what you are
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testing and stakeholder engagement. Collaborate closely with the PhD researcher to connect environmental data analysis with computational design innovation. Participate in fieldwork in Norwegian glacier
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candidates from all backgrounds to join our community. PhD Researcher: AI-Enhanced Adaptive Design for Dynamic Landscapes School of Arts, Design and Architecture – Department of Architecture Location
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experience and ambitions Required Qualifications PhD in Electrical Engineering, Physics, Photonics, Materials Science, or related field Strong theoretical and practical background in semiconductor device
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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are looking for PhD researchers to work on three projects within the group, each led by a newly appointed Research Fellow. Project 1: Autonomous, interpretable and precise nanofabrication in scanning probe
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superconducting qubits and millikelvin electronics Did you recently get your PhD in circuit quantum electrodynamics (cQED) and are now looking into taking the full potential of your skills into use for making new
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. We are now looking for: Three (3) Doctoral Researchers (PhD students) in Machine-Learning-Driven Atomistic Simulations The Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro