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Physics-Informed Synthetic Data for ML-Based BMS

Applications Close: Sep 9, 2026

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Granada, Spain

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Hosting Information

Offer Deadline: Wed, 9 Sep 2026 - 16:00
EU Research Framework Programme: Horizon Europe - MSCA
Country: Spain
City: Granada

Organisation/Institute

Organisation / Company: University of Granada
Department: Electronics and Computer Technology
Laboratory: Electronics for Energy Storage
Is the Hosting related to staff position within a Research Infrastructure? No

Contact Information

Organisation / Company Type: Higher Education Institution
Website: http://www.ofpi.ugr.es; https://gride.ugr.es/en/about/presentation; https://www.ugr.es/

Email: promofpi@ugr.es; rbolivar@ugr.es

State/Province: Granada

Postal Code: 18071

Street: Av. Severo Ochoa, Faculty of Science, Campus of Fuentenueva

Description

MSCA-PF: Joint application at the University of Granada. Department of Electronics and Computer Technology.

Professor Salvador Rodríguez Bolívar, from the Department of Electronics and Computer Technology at the University of Granada, welcomes postdoctoral candidates interested in applying for a Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA-PF) in 2026 at this University. Please note that applicants must comply with the Mobility Rule (for more information about the 2026 call, please consult this link).

Brief description of the institution

The University of Granada (UGR), founded in 1531, is one of the largest and most important universities in Spain. With more than 57,000 undergraduate and postgraduate students and almost 7,000 members of staff, the UGR offers 97 undergraduate degrees, 157 master’s degrees (7 of which are double degrees) and 28 doctoral programmes via its 124 departments and nearly 50 centers. Accordingly, the UGR offers one of the most extensive and diverse ranges of higher education programmes in Spain.

The UGR has been awarded with the "Human Resources Excellence in Research (HRS4R)", which reflects the institution’s commitment to continuously improve its human resource policies in line with the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers. The UGR is also internationally renowned for its excellence in diverse research fields and ranked among the top Spanish universities in a variety of ranking criteria, such as national R&D projects, fellowships awarded, publications, and international funding.

The UGR is one of the few Spanish Universities listed in the Shanghai Top 500 ranking - Academic Ranking of World Universities (ARWU). The 2025 edition of the ARWU places the UGR in 301-400th position in the world and as the 3-8 highest ranked University in Spain, reaffirming its position as an institution at the forefront of national and international research. From the perspective of specialist areas in the ARWU rankings, the UGR is outstanding in Mathematics, Artificial Intelligence and Dentistry & Oral Sciences (ranked between 51th-75th position), Computer Science & Engineering, Education and Hospitality & Tourism Management (between 76-100th position), and in the areas of Food Science & Technology and Business Administration (between 101-150th position). A little lower in the ranking, the UGR also stands out in the areas of Earth Sciences, Law, Management, Nursing, Psychology and Statistics, in which the UGR is positioned in the 151-200th position.

Additionally, the UGR counts with 4 researchers at the top of the Highly Cited Researchers (HCR) list, most of them related to the Computer Science and Mathematics scientific areas. It is also well recognised for its presence in the top 200 Universities in Europe at 83th place.

Internationally, the University of Granada is firmly committed to its participation in the calls of the Framework Programme of the European Union. For the duration of the prevoius Framework Programme, Horizon 2020, the UGR obtained a total of 124 projects with a total funding of more than €30 million. For the current Framework Programme, Horizon Europe, the UGR has obtained 136 projects, so far, with a total funding of more than €38 million.

Brief description of the Centre/Research Group

The TIC105 Research Group, officially known as the Electronic Devices Research Group (GRIDE), is funded within the framework of the Junta de Andalucía and is based at the Universidad de Granada. The group was established in 1985 and has developed a long-standing expertise in the characterization, modeling, and simulation of electronic devices.

Over the decades, its research has focused on modeling semiconductor devices, charge transport, noise phenomena, and advanced electronic structures, later expanding to include organic semiconductors, radiation effects in transistors, sensors, and energy-related devices such as solar cells.

A more recent and relevant research line addresses energy storage systems, particularly the modeling of lithium-ion batteries. This work includes the development of advanced mathematical and computational models for analyzing battery behavior, performance, and lifetime, with contributions in areas such as state-of-charge estimation and aging processes.

The group maintains active collaboration with national and international institutions, participates in competitive research projects, and contributes to technology transfer and doctoral training. Overall, TIC105 represents a consolidated research team with decades of experience in electronic device modeling and a growing impact in emerging fields such as energy storage and sensing technologies.

Project description

Physics-Informed Synthetic Data for ML-Based BMS

Abstract Reliable Battery Management Systems (BMS) are crucial for electric mobility. However, training robust Machine Learning (ML) models for State of Charge and Health is hindered by the scarcity of high-quality, labeled degradation data. This project proposes a hybrid framework using physics-based equivalent circuit models (ECM) to generate synthetic datasets for training advanced ML architectures.

Project Description The core research lies in bridging physical fidelity and computational efficiency. While empirical data from real-world cycling is expensive to obtain, physics-based ECM simulators can model electrochemical phenomena under diverse thermal and loading conditions. We will develop a parameterized circuit-based simulator accounting for internal resistance, capacitive effects, and diffusion. By introducing controlled stochasticity into these parameters, we can generate vast "digital twin" datasets.

These datasets will train ML models, such as Long Short-Term Memory networks or Gated Recurrent Units, adept at time-series battery data. The research investigates "Domain Adaptation" to ensure models trained on synthetic data generalize to real-world cells with minimal fine-tuning.

Expected Impact By reducing reliance on physical testing, this methodology accelerates BMS development. It allows the exploration of edge-case scenarios, like extreme temperatures or fast-charging, difficult to replicate safely in labs. This project aims to enhance the safety, reliability and longevity of energy storage through the synergy of physical modeling and artificial intelligence.