Doctoral Candidate to Develop Gen-ai Cps for Energy Digital Twins

Spindox is a cutting-edge technology consulting company founded in 2007, recognized for its ability to combine research, vision, and pragmatism.
In an era where digital transformation is essential to business competitiveness, we responsibly leverage our resources — people, technological expertise, and contextual awareness — to help our clients navigate change.
Our offering includes industrial research, products, and advanced technology consulting. In particular, our consulting services span several key areas: Vertical Solutions, Emerging Technologies & R&D, Products & Services, User-Centric Experience, Data Intelligence, IT Strategy and Governance, Quality Assurance, Operations & Maintenance, and Cyber Security.
Spindox recorded the highest growth rate in the sector (CAGR 2021-2023 of 25.5%), with 1,300 employees as of December 31, 2023, across ten Italian offices: Milan, Rome, Maranello (MO), Turin, Florence, Cagliari, Baronissi (SA), Trento, Bari, and Ivrea (TO).
Spindox is not just a tech company — it’s a place to explore your potential, push boundaries, and redefine what’s possible. That’s why we’re looking for people who are eager to explore and expand their knowledge. Our culture values individual uniqueness and rewards merit. We are looking for people with imagination and passion.
Job Information
**Organisation/Company**: Spindox Labs srl
**Research Field**: Computer Science, Artificial Intelligence, Data Engineering, Cyber-Physical Systems, Energy CPS
**Researcher Profile**:
**Positions**: PhD Position
**Country**: Italy
**Application Deadline**: 05/12/2025 - 12:00 (Europe/Berlin)
**Type of Contract**: Permanent
**Job Status**: Full-time
**Hours Per Week**: 40
Is the job funded through the EU Research Framework Programme?: Horizon Europe - MSCA - Doctoral Network
**Marie Curie Grant Agreement Number**: 101226624
Is the Job related to staff position within a Research Infrastructure?: No
Offer Description
The Role
**Position Title**: Data & AI Engineer - Digital Energy Twin for Energy CPS
Scientific Context
Objectives
Design and implement Digital Energy Twin models for real-time monitoring, forecasting, and interaction within energy CPS.
Develop AI/ML pipelines for time-series forecasting, demand flexibility, anomaly detection, and proactive decision-making.
Integrate eco-cognition and explainability models developed in collaboration with UAntwerp into energy CPS.
Fuse multi-modal data (energy production/consumption, IoT sensors, mobility, environmental data) into predictive and adaptive models.
Expected Results
Novel AI-driven Digital Twin prototypes for energy grid resilience, load management, and demand response.
Validated proactive and explainable CPS solutions for the Digital Energy Twin use case.
Contributions to GREET’s research agenda on transparent, proactive, and eco-cognitive CPS.
Open-source tools, demonstrators, and publications aligned with GREET’s dissemination and training goals.

**Responsibilities**:
Conduct applied research at the intersection of AI, IoT, and CPS, under joint supervision from Spindox and UAntwerp.
Develop data engineering pipelines and testbeds for Digital Energy Twin demonstrators.
Contribute to GREET deliverables, reports, and standardization activities.
Publish in top-tier journals and conferences; contribute to open-source projects.
Participate in GREET training events, workshops, and industry collaborations.
Support knowledge transfer between academia and industry, including public engagement and dissemination.
Profile
**Education & Background**:
Master's degree in computer science, AI, Data Engineering, Electrical Engineering, or related field.
Knowledge of AI/ML for time-series forecasting, anomaly detection, clustering.
Familiarity with IoT, CPS, and digital twin architectures.
**Technical Expertise**:
Python, Pandas, Scikit-learn, PyTorch
Distributed computing and data engineering stacks
Cloud-edge deployments, containerization, real-time simulation tools
Multi-modal sensor integration
**Research & Innovation Experience**:
Experience in EU-funded projects (H2020, MSCA, Horizon Europe) a plus
Track record of publications, deliverables, or open-source contributions
**Desirable Skills**:
Familiarity with LLMs, agentic AI, semantic technologies (RDF, knowledge graphs)
Awareness of dataspaces and data governance frameworks (e.g., Eclipse Dataspace Connector)
**Soft Skills**:
Analytical and problem-solving skills
Independent work in interdisciplinary, international teams
Excellent oral and written communication
**Eligibility**:
What we offer
- The planned start date is March 2026 or as soon as possible after that date.

How to Apply
**Applications must include**:
Motivation letter highlighting expected impact on your future career.
Academic CV, including transcript and publications.
Two reference letters with contact details.
English proficiency certificate.
Short research proposal (max. 4 pages, excluding references) integrating:

- Propose a topic that integrat