Join Us
Explore career opportunities and open positions within the EDT research program. We are always looking for talented researchers, engineers, and students to join our interdisciplinary team working on cutting-edge digital twin technologies.
Current Opportunities
36 available positions
Location-aware digital twins for wireless communication networks
This post-doctoral contract develops location-aware digital twins of wireless communication networks, using self-supervised channel charting to derive location information directly from existing communication signals.
- PhD in digital communications, machine learning or signal processing
- Familiarity with self-supervised machine learning
- +2 more requirements
Iterative design of Socio-technical system Digital TWINs by AI-Augmented process mining
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- Fluency in English and French
Monitoring and Verification of Applications involving Digital Twins.
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- Fluency in English and French
Data Assimilation with Model Bias Correction for Digital Twin Monitoring of Complex Systems
This PhD designs bias-aware data assimilation methods for digital twins of large, complex, high-dimensional systems, combining model reduction and AI to improve accuracy and robustness against model bias, validated on a Cetim pressure-vessel demonstrator.
- Master degree in Applied Mathematics, Computational Mechanics, or Data Science
- Interest in numerical methods for data assimilation and uncertainty quantification
- +2 more requirements
Digital Twins for Wireless Networks
This PhD investigates the design of digital twins for wireless networks, aiming to develop frugal data collection and closed-loop control mechanisms that translate predictions into actionable adaptations within low-power wireless systems.
Frugal and AI-Enhanced Data Governance for Reliable Digital Twins
Brief summary of the position and research focus
PhD Position - Engineering Digital Twins Dedicated to 2D and 3D Input and Output Technologies of Interactive Systems: application to the digital twin of Luxembourg Electric Grid
PhD position in Human-Computer Interaction focusing on engineering 2D and 3D input and output technologies for digital twin systems
- Master's degree in Computer Science, HCI, or related fields
- Strong programming skills e.g. Java
- +2 more requirements
AI-Assisted Model-Driven Security Engineering for Digital Twins: Toward an Automated Round-Trip Framework
This PhD thesis has the objective to address the challenges of modeling Digital Twins by integrating Artificial Intelligence (AI) assistance, enhanced security modeling, simulation and round-trip feedback.
Improving Sustainability in the Physical-to-Digital Twin Continuum: A Middleware Framework for Adaptive Deployment
PhD position in the area of sustainable middleware for digital twins.
- Master degree in relevant field
- Experience with digital twins
- +2 more requirements
Automatic construction of a digital model from real-world scenes
Extraction of the geometry, the kinematics, and the mechanical properties using machine learning of a single object from videos or photos.
- Master degree in relevant field
- Experience with digital twins
- +1 more requirements
Modeling Interaction Scenarios for Digital Twins in Mixed Reality
The effective use of digital twins requires interactive scenarios capable of organizing the system’s objectives, roles, activities, and behaviors within a real-time framework. This requirement is further heightened in mixed reality, where the user interacts with both digital representations and a physical environment, necessitating the joint design of the business model, interaction, and scenario execution.
Visualization of the Plausibility and Bias for Data Resources used in a Geographic Digital Twin
In this PhD research project we will investigate how to automatically classify the plausibility in datasets collected for a geographic or otherwise spatial data, and how to visualize it. We will rely on past results that detected data biases and data errors based on a manual analysis, and will investigate how to use machine learning models to automate this process. In addition, we will investigate how best to depict the different types and degrees of data bias, data imprecision, and data error.
- Master degree in computer science or related field
- Interest in interactive data visualization and analysis
- +4 more requirements
A software engineering approach to ease the development and to ensure the usability of interactive digital twins
By its very nature, a digital twin strongly relies on data visualization and user interactions. Building such interactive digital twins from scratch and in a craft way is time-consuming and may prevent the generalization of DT as industrial tools limiting the benefits to be expected from their deployment. The goal of the PhD is to propose novel software engineering approaches to ease and support the development of reliable and usable interactive digital twins
Supporting transitions for interacting in Digital Twins.
We are seeking a motivated PhD candidate to join the PC5 team working on Human-Digital Twin Interactions. This position focuses on developing innovative immersive solutions to support transitions between the physical referent (PR) and the digital replica (DR) of a Digital Twin (DT).
- Master degree in HCI, VR, Computer Science or other relevant fields
- Experience with AR / VR technologies (software, hardware)
- +2 more requirements
Methodology for Engineering Digital Twins
The goal is to define a generic methodology that covers the whole digital twin lifecycle.
- PhD in computer science
- Programming skills
- +2 more requirements
Aggregation of digital twins in the manner of Systems of Systems
The goal is to develop a System of Systems approach from the design stage onwards. This will enable each component of the digital twin to be identified in relation to a physical system functionality, and their assembly will result in a complete digital twin through aggregation, whose lifecycle management will be controllable, just like the physical system.
Exploring Alternative Evolutions of Digital Twins
PhD position in Human-Computer Interaction and Virtual Reality focusing on immersive interfaces for digital twin systems
Federation of data and models to define digital twins
The digital twin is a repository of knowledge that must be modeled and constructed from highly heterogeneous sources of information. This heterogeneity has several sources: the nature of the information, but also its temporality (real time, futures, pasts). The aim of this thesis is to overcome this obstacle of heterogeneity.
Modeling the construction of digital twins
The goal is to develop an environment for building and executing digital twins based on a digital twin model and its lifecycle.
Composing and Configuring Digital Twin Architectures to Meet User Requirements (Energy, Performance, Budget)
This PhD project investigates methods for composing and configuring digital twin architectures in order to meet user requirements under multiple non-functional constraints such as energy consumption, performance, and budget.
Composing DTs with Variability, Fidelity and Uncertainty
This PhD project aims to propose concepts, methods and tools to allow the composition of digital twins components with an explicit handling of Variability, Fidelity and Uncertainty.
- Master or Engineering degree in Software Engineering
- Experience with modeling (SySML, UML,...)
- +2 more requirements
Compositional Hybrid Digital Twins Models
PhD position on compositional hybrid modeling and digital twin frameworks
- Master's degree in Computer Science, Computational Biology, Applied Mathematics, or related field
- Background in modeling complex systems or machine learning
- +3 more requirements
Distributed Abductive Reasoning for Self-Explaining Digital Twins
PhD position on explainable and distributed reasoning mechanisms to bridge the reality gap in hybrid digital twins
Formal Engineering Methods for Digital Twin Development
PhD position on formal engineering processes and methods for building reliable multi-paradigm digital twins
- Master's degree in Computer Science, Software Engineering, or related field
- Strong background in formal methods, modeling languages, or system engineering
- +3 more requirements
Integration and synchronization of digital twins for co-simulation
This PhD project aims to propose a framework enabling the integration and synchronization of heterogeneous digital twins for reliable co-simulation. The objectives consist to consider how heterogeneous DT can be integrated into a coherent co-simulation framework.
Interconnection of digital twin knowledge
Digital twins will need to represent a variety of knowledge about territories and related data. It is therefore not possible to rely solely on a single unifying model, but must be able to interact with a variety of heterogeneous representations. This PhD project aims to manage the diversity of knowledge and viewpoints.
- Master degree in Software Engineering
- Experience with digital twins
Interpretable and Robust Machine Learning for Physics-Based Numerical Simulations
PhD position on statistical methods to improve interpretability and robustness of machine learning models used to accelerate physics simulations
- Master's degree in Applied Mathematics, Statistics, Computer Science, or related field
- Strong background in statistics, machine learning, or scientific computing
- +3 more requirements
Model Management for Explainable and Traceable Hybrid Model Management for Digital Twins
PhD position on explainable and traceable management of hybrid physics-based and machine learning models in digital twins
Navigating through the temporal aspects of the digital twin
PhD position in Human-Computer Interaction and Virtual Reality focusing on immersive interfaces for digital twin systems
Smart Scenario Exploration for Digital Twins through Validity Envelopes
PhD position on model interoperability and scenario exploration for environmental digital twins, focusing on validity envelopes for scientific models
Structural Methods for Mixed Model/Data Digital Twin Engineering
PhD position on structural analysis methods for data based diagnostic of physics-based digital twin models
- Master's degree in Computer Science, Applied Mathematics, Control Systems, or related field
- Strong background in mathematical modeling and dynamical systems
- +3 more requirements
Technical Lead – Digital Twin Platform (Responsable Technique EDT)
Technical Lead role to drive architecture and delivery of a cloud-native digital twin platform across a national research consortium, coordinating multidisciplinary teams and key technology decisions. Contract type: 3-year contract, renewable.
- Master's or PhD in Computer Science, Software Engineering, Systems Engineering, or a related discipline (or equivalent professional experience).
- Demonstrated experience leading large-scale software projects.
- +7 more requirements
Hybridization of Simulation and Learning Models in Digital Twins for Mechanical Systems
PhD position on hybrid modeling approaches combining simulation and machine learning for digital twins in mechanical engineering.
- Master's degree in Computer Science, Artificial Intelligence, or related field
- Strong background in AI or reasoning systems
- +3 more requirements
Agents as Run-time Exploratory Programmers for Digital Twins
This PhD investigates how LLM-enabled autonomous agents can act as run-time exploratory programmers for digital twins, enabling live what-if scenario exploration without manual implementation of complex language support or state migration, by directly interacting with executing systems through existing interfaces and continuous feedback.
Model Hybridization in Digital Twins for Mechanical Engineering
CETIM-funded PhD on hybrid modeling for digital twins of mechanical equipment, combining model simulation and data science to enable predictive maintenance, optimization and decision support on the CETIM JNEM thermal-hydraulic loop.
Large Language Models for Earth Observation Digital Twins
Postdoctoral position at CNES — Design and evaluation of LLM/VLM approaches for Earth digital twins.
- PhD in remote sensing, artificial intelligence, geospatial science, computer science, or related discipline
- Strong background in deep learning and foundation models
- +1 more requirements
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