Job offer

With the growing need for organizations to increase business profitability and strengthen their position in a highly competitive market, the demand for cloud services and resources has increased significantly. In the digital era, no organization can realistically envision evolving its information system or exposing its services without relying on cloud technologies. Beyond this, leveraging services from multiple cloud providers has become a natural choice for organizations seeking to deliver highly available services while ensuring rapid recovery and reduced operational costs.

New requirements are also emerging for computing and storage capabilities at the edge, as well as for the numerous Internet of Things (IoT) devices that underpin smart cities, Industry 4.0, and connected vehicle networks. The resulting ecosystem-the Cloud-Edge-IoT continuum-is characterized by highly heterogeneous infrastructures and multi-layered applications, for which monitoring, anomaly detection, and resource usage prediction are fundamental services to guarantee application quality of service and security.

At the same time, with the proliferation of cyberattacks, cyber risk has become one of the major business risks facing organizations. To assess their own security posture, as well as that of their subsidiaries and suppliers, companies require efficient, automated, and accessible solutions capable of addressing the shortage of cybersecurity expertise. Such assessments must be accurate, continuous, and transparent, particularly in the context of new European regulations that reinforce requirements for managing third-party cyber risks.

Achieving these objectives is possible but far from straightforward, especially in a highly monopolized cloud market where users remain constrained to consume services from a single provider, leading to strong vendor lock-in. Our research team has laid the foundations for addressing this challenge by proposing a cloud-provider-independent model for describing user requirements and service offerings, together with a service discovery approach. The next challenge is to design techniques enabling the automated composition of services from multiple providers, a key step toward satisfying complex and emerging user requirements in distributed environments.

Within this broader context, the team's research aims to develop methods for automating service composition across the Cloud-Edge-IoT continuum, generating the corresponding deployment models, monitoring their execution, and continuously assessing the cyber posture of organizations.

ACTIVITIES:

• Definition of a methodology for the automated generation of deployment models for composite services, integrating execution monitoring, anomaly detection, and resource usage prediction to facilitate the orchestration and operation of applications in complex and heterogeneous environments, including large-scale experimental infrastructures
• Development of software components and tools enabling the integration of monitoring and anomaly detection capabilities into existing infrastructures and applications, leveraging innovative methods adapted to the increasing complexity of software stacks across the Cloud-Edge-IoT continuum
• Design of a continuous cyber posture assessment approach tailored to organizational information systems, enabling greater automation of security diagnostics and improved integration into operational processes, from small and medium-sized enterprises (SMEs) to large organizations
• Development of automated security assessment mechanisms based on dynamic indicators and system analysis techniques to enhance the early detection of vulnerabilities and risks, in response to the requirements of current European regulations (NIS2, DORA)
• Implementation of software solutions supporting the integration of continuous assessment capabilities within heterogeneous environments, ranging from SMEs to large enterprises, through simple, cost-effective, and fully automated solutions that reduce the workload of security teams
• Validation of the proposed approaches through industrial use cases representative of the Cloud-Edge-IoT continuum, demonstrating their effectiveness, robustness, adaptability, and ability to continuously improve both quality of service and the cyber posture of organizations, * Working conditions: Teleworking possible, restaurant and cafeteria on site, accessibility by public transport (with employer's participation) or close to main roads, staff association and sports association on campus

Research Field Computer science

Education Level PhD or equivalent

Skills/Qualifications

Essential skills, knowledge and experience:

• Strong knowledge of Generative Artificial Intelligence (Generative AI)
• Solid experience and expertise in cloud services and cloud computing technologies
• Proficiency in programming with Python, Java, C, and C++
• Fluent written and spoken English

Advantageous skills, knowledge and experience:

• Experience in machine learning
• Experience with orchestration tools for deployment and configuration of infrastructures and services (e.g., Docker, Kubernetes, Terraform, etc.)
• Experience with tools and technologies related to blockchain and business process management (BPM)

Abilities and skills:

• Ability to work as part of a team on national or international research contracts, in collaboration with academic and industrial partners
• Good interpersonal skills
• Reactivity, initiative and rigor
• Curiosity
• Interest in new technologies
• Autonomy

Languages ENGLISH, Computer science