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Field
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. Quantum Computation with spin qubits: You will have the opportunity to delve into the theoretical aspects of solid-state quantum computing in spin qubits platforms. This includes gaining expertise in device
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passionate about linking atomistic processes to device performance through computer simulations? Are you fascinated by designing next-generation semiconductors with quantum-mechanical methods enhanced by AI
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are looking for a passionate postdoctoral researcher to join us at the Bosco group and advance theoretical research in solid-state quantum computation, with a focus on spin-based platforms. Our team is actively
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the Amsterdam School of Communication Research (ASCoR) at the Faculty of Social and Behavioural Sciences, University of Amsterdam. ASCoR brings together experts across four program groups - Persuasive
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research on how media and technology shape society. For this project, you will be officially embedded in the Youth & Media Entertainment (YME) program group. YME focuses on the role of emerging technologies
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information science. Good knowledge of mathematical and theoretical physics methods of describing random processes and random fields. Experience with analytical and/or numerical methods for modelling qubit dynamics
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, mathematics, or a related field. Strong background in quantum physics, mathematics, and quantum information science. Good knowledge of mathematical and theoretical physics methods of describing random processes
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. This proposal should be uploaded to the "additional documents" field of the "application information" section. You should have: Sound theoretical knowledge of quantum computing and computing science; including
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, interdisciplinary and open work environment; access to high-performance computing infrastructure and unparalleled EO and technology expertise; a unique opportunity to work on innovative solutions to address global
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, chemistry, computational science, or a related field. Strong expertise in at least two of the following: density functional theory (DFT)/many-body methods, molecular dynamics (MD), machine learning (ML