Sd-25136- Post-doc On Data and Model Harmonization for Digital Twin Systems

Description
**Temporary contract | 24 months | Belval**:
**Are you passionate about research? So are we Come and join us**:
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

LIST coordinates a National Centre of Excellence in Research (NCER) for a Data-Driven Energy Transition (D2ET). This initiative aims at supporting**Luxembourg's energy transition through a nation-wide digital platform, built together with public and private stakeholders in the Energy sector. Such a platform puts together multidisciplinary data and models covering different aspects of the energy transition, including energy infrastructure, market design, regulatory constraints, social and environmental impacts.

Within the project, we aim at addressing the research challenges associated with the design and operationalization of a nation-wide platform including data collection and energy-related data and model harmonization aspects, through a postdoctoral position.

You will join a collaborative and multidisciplinary team and will act as a reference expect on data and model harmonization across domains, including semantic and technical interoperability of data and models towards its integration into a common digital twin platform.

**How will you contribute?**

You will be designing and implementing appropriate methodologies and technical frameworks to harmonize and integrate data and models from core research work-packages into a common decision-support platform. This involves providing model management support, with concrete prototype, by analyzing and understanding data through models—both static and dynamic representations that capture the knowledge and behavior of a physical system.

The role includes characterizing and engineering diverse models and their relationships with underlying data coming from different stakeholders pertaining to the key impacted domains. Additionally, model engineering will consider the lifecycle of the Digital Twin (DT), addressing both its progressive development and the evolution of the physical system it represents.

Key research areas include ensuring the consistency and evolution of heterogeneous DT models, accounting for variations in purpose, precision, granularity, completeness, and nature (e.g., ML/AI-based models, business rules, human knowledge vs. data-driven insights, and process models).

**Main Responsibilities**:

- Design and implement a model-based management infrastructure to support integration and harmonization of data and models in a heterogeneous context (i.e., different data source from human to technical, from knowledge to generative AI models).
- Collaborate with software engineers to integrate the management infrastructure within the Digital Twin platform delivered in the context of the project.
- Collaborate with the project’s stakeholders (data scientists, domain experts) via participation into Living Labs, to integrate/harmonize knowledge and models (e.g., including simulation, prediction).
- Enable the evolution of integrated data/models all along the Digital Twin lifecycle
- Ensure the consistency of integrated data and models with regard to potential evolution of the physical system it represents.
- Support project planning, execution, and reporting.
- Write technical documentation, research reports, and contribute to scientific dissemination (e.g., conferences, workshops, white papers).

**Required Qualifications**
- PhD degree in System Engineering, Software Engineering, Model-Driven Engineering or a related technical field.
- Strong proficiency in model-driven or model-based system design, includes domain specific languages, data and system modelling, model transformations.
- Experience in formulating and presenting innovative/ scientific/ technological concepts.
- Excellent skills in communication and interaction with scientific and industrial stakeholders.
- Experience in the development and maintenance of prototypes.
- Experience with open-source software ecosystems.
- Excellent problem-solving skills and the ability to work both independently and in a team.

**Preferred Skills**
- Experience with data management, data discovery, data collection, data exploration.
- Familiarity with Git-based workflows and collaborative development practices.
- Experience with generative AI in a system engineering context.
- Familiarity with various data-based, data collection and data workflow
- Experience working with energy systems, simulation tools, or digital twin technologies.
- Background in research-to-industry integration.

**Language skills**
- Good level both written and spoken English

**Your LIST benefits**
- An organization with a passion for impact and strong RDI partne