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- Institute of Photonic Sciences
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line focused on Negative Triangularity Leadership role: control and data acquisition systems for the SMART tokamak Develop and apply numerical simulations, with emphasis on: o Plasma equilibrium o
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of advanced photonic integrated circuits (PICs) for optical switching and processing applications. Key Responsibilities: The selected candidate will be expected to: Design, simulate, and optimize integrated
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sheets and amorphous graphene nanoribbons generated by collaborating teams at University of Ankara. They will be trained in the LSQUANT methodology and in the numerical tools developed at ICN2 to simulate
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screening, and automated experimentation to accelerate materials discovery and optimization. The researcher will work across the groups of Prof. José Berrocal and Prof. Carla Casadevall at ICIQ and interact
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modelling and numerical relativity. The group comprises PI Alicia Sintes, a further ten faculty members and a large number of post-doctoral researchers and PhD students. The group is a member of the IAC3
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reliability measurements. Contribute to the development of automated characterization platforms and measurement procedures. Collaborate with device designers and fabrication partners to optimize device
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extensive electromagnetic modeling to optimize the waveguide structures for minimal loss, efficient confinement, and effective mode matching with external optical components. Particular attention will be
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position is hereby announced for a Recognised Researcher (R2A) (Postdoctoral Researcher) to carry out the project "EMPOWER-HFpEF: Early Multimodal Program to Optimize Well-being, Functional Capacity and
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with the supervisor, with potential avenues including generative models, optimization tasks, or other specific applications. The candidate will work in the context of the project ML-QSIM, a 4-year, 2M
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direction and publication. Research activities may include AI-assisted target discovery and biologic design, protein engineering and developability optimization, mechanistic studies in metabolic disease