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IBM announced detailed plans today to build an error-corrected quantum computer with significantly more computational capability than existing machines by 2028. It hopes to make the computer available to users via the cloud by 2029. 

The proposed machine, named Starling, will consist of a network of modules, each of which contains a set of chips, housed within a new data center in Poughkeepsie, New York. “We’ve already started building the space,” says Jay Gambetta, vice president of IBM’s quantum initiative.

IBM claims Starling will be a leap forward in quantum computing. In particular, the company aims for it to be the first large-scale machine to implement error correction. If Starling achieves this, IBM will have solved arguably the biggest technical hurdle facing the industry today to beat competitors including Google, Amazon Web Services, and smaller startups such as Boston-based QuEra and PsiQuantum of Palo

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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors, and more than 4 500 other faculty and staff working on our dynamic campus in Espoo, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. 

The School of Chemical Engineering is one of the six schools of Aalto University. Department of Chemical and Metallurgical Engineering focuses on sustainable utilization of raw materials, designing and developing more efficient processes for new materials and products. We as chemical engineers

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Synopsis

The Human Networks and Data Science program (HNDS) supports research that enhances understanding of human behavior by leveraging data and network science research across a broad range of topics. HNDS research will identify ways in which dynamic, distributed, or heterogeneous data can provide novel answers to fundamental questions about individual or group behavior. HNDS is especially interested in proposals that provide data-rich insights about human networks to support improved health, prosperity, and security.

HNDS has two tracks:

(1) Human Networks and Data Science – Infrastructure (HNDS-I). Infrastructure proposals will address the development of data resources and relevant analytic techniques that support fundamental Social, Behavioral and Economic (SBE) research. Successful infrastructure proposals will construct, within the financial resources provided by the award, databases or relevant analytic techniques and produce a finished product that will enable previously impossible data-intensive research in the social sciences. The

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NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

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