Quantum computation exploits microscopic properties of matter to achieve speedups over classical computation. However, existing as well as near- to mid-term quantum computers lack fault tolerance and are limited in size. As such, they are referred to as noisy intermediate-scale quantum (NISQ) devices. NISQ processors function primarily as purpose-built quantum calculators for specific tasks, rather than general-purpose computers. Identifying industrial workloads that are amenable to NISQ computing is presently a major interdisciplinary quest.

Cloud computing offers virtually unlimited resources in CPU, memory, and bandwidth, under a service agreement scheme. Operators leverage on this model to achieve economies of scale, by hosting as much customers as possible on such infrastructure. The detected gap is that the Communication Service Providers (CSP) must take into consideration trust as a parameter into the service offering to its customers. This way, customers obtain tools and design capabilities to choose a cloud service offer according to trust-related internal security policies.

Artificial intelligence (AI) has transformed our way of perceiving and interacting with technology, by providing state-of-the-art solutions for challenging problems across the tech-spectrum. The main objective of this cluster of projects is to investigate, develop, adapt, integrate and evaluate state-of-the-art machine learning (ML) techniques, which are suitable for modeling and prediction using datasets collected for complex real-world telecommunications applications. Given the applications of interest for Ericsson Inc., we will focus on ML techniques:
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By virtualizing all the various appliances in the network, Virtual Network Functions (VNF) became a key enabler for the coming 5G infrastructure and nowadays a major shift is under way bringing an evolution to cloud-native VNF. In the latter operational model, applications are decomposed into microservices running inside containers to enable automated installation, configuration and scaling with the dynamic network requirements beside self-healing and automated upgrading and updating of the VNFs.

Ce projet vise à étudier et développer une preuve de concept d’un bouchon d’oreille pour chevaux. Les bouchons d’oreille sont utilisés pour réduire le niveau sonore des chevaux afin de réduire les distractions et d’améliorer leur concentration. Toutefois, le niveau d’atténuation des bouchons disponible sur le marché est limité. De plus, on dénote un intérêt grandissant pour le monitorage des signes vitaux des chevaux. Ceci permet d’assurer la santé des chevaux dans plusieurs domaines tel que le dressage, les courses et les calèches.