Doctoral Candidate to develop Gen-AI CPS for energy Digital Twins
Descrizione dell'offerta
Doctoral Candidate to develop Gen-AI CPS for energy Digital Twins
Spindox Labs srl is seeking an experienced doctoral candidate (DC) to join the Marie Skłodowska-Curie Doctoral Network GREET – Generative Explainee-aware Explainability and Transparency in Proactive Cyber-Physical Eco-Environments.
Role
The DC will contribute to the design, development, and validation of Digital Energy Twin (DET) solutions in energy networks, integrating AI, IoT, and cloud-edge computing to enable resilient, adaptive, transparent, and explainable cyber-physical systems (CPS).
The position will bridge academic excellence at the University of Antwerp (UAntwerp – IDLab) and applied research at Spindox Labs, focusing on the energy domain while contributing to GREET’s core objectives of Generative Learning Cognitive Services (GLCS), eco-cognition, proactivity, and explainee-aware explainability.
Selected candidates will undertake secondments at Edinburgh Napier University (3 months) and the University of Antwerp (4 months).
Scientific Context
The research aligns with GREET’s vision of next‑generation CPS combining eco‑cognition, explainability, and proactive decision‑making across cloud‑edge‑IoT environments.
Research Objectives and Expected Results
- Design and implement real‑time Digital Energy Twin models that monitor, forecast, and interact within energy CPS, producing AI‑driven prototypes for grid resilience, load management, and demand response.
- Develop AI/ML pipelines for time‑series forecasting, demand flexibility, anomaly detection, and proactive decision‑making, delivering validated, explainable CPS solutions.
- Integrate eco‑cognition and explainability models from UAntwerp to enhance transparency and adaptability, advancing GREET’s research agenda.
- Fuse multimodal data from energy production, consumption, IoT sensors, mobility, and environmental sources to create predictive and adaptive models, leading to open‑source tools, demonstrators, and publications.
- Apply neuro‑symbolic learning and generative explainability frameworks to push the boundaries of explainable, adaptive systems and produce meaningful research contributions.
Duties and 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.
- Collaborate with GREET doctoral candidates on shared research challenges: eco‑cognition, explainability, and proactivity.
- Contribute to GREET deliverables, reports, and standardisation 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 and Background
- Master’s degree in Computer Science, AI, Data Engineering, Electrical Engineering, or a related field.
- Strong knowledge of AI/ML techniques for time‑series forecasting, anomaly detection, and clustering.
- Familiarity with IoT, cyber‑physical systems (CPS), and digital twin architectures.
Technical Expertise
- Proficient in Python, Pandas, Scikit‑learn, and PyTorch.
- Experience with distributed computing and data engineering stacks.
- Knowledge of cloud‑edge deployments, containerisation, and real‑time simulation tools.
- Expertise in multimodal sensor integration.
Research and Innovation Experience
- Previous experience in EU‑funded projects (H2020, MSCA, Horizon Europe) is a plus.
- Proven track record of publications, deliverables, or open‑source contributions.
Desirable Skills
- Familiarity with large language models (LLMs), agentic AI, and semantic technologies (e.g., RDF, knowledge graphs).
- Awareness of dataspaces and data governance frameworks (e.g., Eclipse Dataspace Connector).
What We Offer
- Competitive remuneration in accordance with MSCA allowances, plus funding for technical and personal skills training and participation in international research events for the full 36‑month grant duration.
- Planned start date March 2026 or soon after.
How To Apply
Apply online up to 05 December 2025 16:00 Europe/Rome through Spindox’s job platform using the “Submit your CV” form. Upload a single PDF containing:
- 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) integrating the position’s core research with at least one target domain. The proposal must include problem statement, expected novelty/impact, brief approach, evaluation plan, and alignment with Spindox Labs’ focus.
Applications will be reviewed as soon as possible after the deadline. Candidates who pass pre‑selection will be notified of the next step(s) in the selection procedure.
Questions about the application form: For job‑specific questions: Luca Capra and Mario Conci
Eligibility
- Candidates must not have resided or worked in Italy for more than 12 months in the 36 months immediately prior to recruitment.
- Candidates must not already hold a doctoral degree.