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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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a dynamic, international research environment. Your experience and ambitions Required Qualifications PhD in Electrical Engineering, Physics, Photonics, Materials Science, or related field Strong
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experience and ambitions We are seeking a candidate with: Educational background PhD in Architecture, Landscape Architecture, Computational Design, Computer Science, Urbanism, or a closely related field
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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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ambitions We are seeking a candidate with: Educational background PhD in Architecture, Landscape Architecture, Computational Design, Computer Science, Urbanism, or a closely related field. Specialization in
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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
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reaching the milestones including the supervision of PhD, MSc, and BSc theses Collect and archive reporting data from your peers to keep track on the progress Coordinate our local efforts with our national
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estimating system performance, capacity, and operational requirements under various industrial scenarios. What We Are Looking For (Your Profile): Required Qualifications: A master's or PhD in Energy Systems
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-matter BEC in a telecom range Phys. Rev. B 110, 134321 (2024) Your role and goals The successful candidate is expected to lead the experimental effort with a team of PhD and master’s students and