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Description Mission: Lead the N3Cat group's chip group and work in the field of emerging and advanced computing technologies, including new devices, circuits and architectures for classical and quantum
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme in computer science . Excellent oral and written communication skills in English. You must comply with
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science » Computer systems Computer science » Modelling tools Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 May 2026 - 23:00 (Europe/Paris
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State University of New York University at Albany | Albany, New York | United States | about 6 hours ago
to the university, college, and department. Key areas of interest within this focus on computing and artificial intelligence include, but are not limited to, neural networks, error correction, and system architecture
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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Doctoral Researcher in Building Acoustics with a strong interest in historical construction and twentieth-century architecture in Finland We are looking for a Doctoral Researcher to join a new
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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC‑PF) computations, potentially facilitating real‑time contingency analysis, rapid design
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scientific data, model architectures, and training dynamics influence scientific predictions. You will join a vibrant research environment at TU/e at the intersection of AI, scientific computing, and
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architecture. The research focus of this PhD position is the design of performant and energy-efficient Edge Artificial Intelligence (AI) accelerators. Such accelerators may be either tightly integrated with