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Field
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on distributed quantum computing. The project aims to develop superconducting
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2-yr postdoc on Forecasting Biosphere-Scale Effects of Ecological Novelty Using Species Distribut...
The Department of Biology, Aarhus University invites applications for a 2-year postdoc position on: Forecasting biosphere-scale effects of ecological novelty using species distribution and
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and spatial distribution” in the Research Unit Coastal Seas and Society until the 30.11.2027 and a percentage of 100% (40h/week), subject to the funding of the project. Remuneration is paid in
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ICFO is offering a postdoctoral position to a well-qualified, highly motivated and dynamic young scientist who wishes to enhance his/her scientific career in a friendly and stimulating environment. The successful candidate will be joining the Optoelectronics group led by Prof. Dr. Valerio...
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involves working on projects related to scientific workflow management, distributed systems, and the application of AI technologies and solutions to the management of scientific workflows in distributed
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the emergence of edge computing, data storage will become more geo-distributed to account for performance or regulatory constraints. One challenge is to maintain an up-to-date view of available content in such a
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
in the Amazon and on how these relate to the distribution of vector-borne diseases in the Amazon forest. The post holder will carry out their research, advised by the PI and Dr. Milton Barbosa from
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seeking a postdoctoral researcher with expertise in distributed intelligence, reasoning models, LLMs, workflow management, and distributed systems to contribute to the development of advanced decentralized
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. Ahmed Sayed. The main project (KUber) is, EPSRC-funded, aiming at building novel distributed architectures to facilitate the exchange and delivery of acquired knowledge among machine learning entities
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related