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needs, we may support flexible and hybrid work arrangements. Options will be discussed during the interview process? Responsibilities The division runs several research projects in parallel. The candidate
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. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 2 months ago
description: The Scientific Computing Center is the Information Technology Center of KIT. The Research Group Exascale Algorithm Engineering of SCC works at the interface of algorithmics, parallel computing, and
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for Regional Environmental Nitrogen Measurements (Onderzoeksprogramma Regionale Omgevingsmetingen Stikstof, OROS) is essential, as there are clear parallel questions. The project provides strong support for your
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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, space, modal content, etc. However a systematic analysis of the potential and trade-offs of applying photonic parallelism to computing is still lacking. This PhD project aims to get an in-depth
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applicants only References "Lab website https://cellplasticity.weebly.com/ Recent work from the lab Plygawko, A.T., Adams, J., Richards, Z. and Campbell, K. (2025) A hormonally regulated gating mechanism
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redox balance. Our studies explore how p53 integrates metabolic cues by acting as both a sensor and regulator of cellular metabolism. In parallel, we are identifying metabolic changes that promote tumor
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administrative duties within the department, faculty and university. The department uses Swedish and English in parallel. The professor should be able to perform the majority of their tasks in English. However, as
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, conducting performance assessments and benchmarking case studies, and helping codes to transition into the era of accelerate compute. You will be embedded into the SHAREing (https://shareing-dri.github.io