PbJob Title: /b Battery Modelling Researcher (Physics-Based AI Models) /ppbLocation: /b Barcelona, Spain /p pbPosition Overview /b /ppWe are seeking a highly motivated and skilled researcher to join our bSmart Battery Unit /b in Barcelona. The successful candidate will work at the intersection of electrochemical modelling, data-driven methodologies, and real-world battery systems /ppbr/ppThis role is focused on the development of advanced battery models that can be translated from research environments into practical applications, including Battery Management Systems (BMS), edge devices, and cloud-based platforms. The candidate will contribute to cutting-edge national and European RD projects, while supporting the transition of innovative modelling approaches into scalable, production-ready solutions /ppbr/ppbKey Responsibilities /b /pulliDevelop and implement physics-based battery models, with a strong focus on electrochemical modelling (e.g., P2D and reduced-order models) /liliDesign, develop, and validate data-driven and hybrid models for State of Charge (SoC), State of Health (SoH), and Remaining Useful Life (RUL) estimation /liliWork with and extend frameworks such as PyBaMM for simulation and model development /liliTranslate advanced models into deployable solutions for BMS, including embedded (edge) and cloud-based architectures /liliAnalyse experimental and real-world battery data for model calibration and validation /liliContribute to the development of Digital Twins for battery systems /liliCollaborate with multidisciplinary teams across Artificial Intelligence (AI), Internet of Things (IoT), and hardware domains /liliSupport proposal preparation and technical development in European RD projects (e.g., Horizon Europe) /li /ul pbRequired Profile /b /pulliStrong background in battery modelling, including: /liliElectrochemical models (essential) /liliPhysics-based modelling approaches /liliProficiency in Python for scientific computing /liliHands-on experience with PyBaMM /liliSolid understanding of battery systems and Battery Management Systems (BMS) /liliExperience working with experimental data and model validation /liliDegree in Electrical Engineering, Chemical Engineering, Physics, or a related field (MSc or PhD preferred) /lilibFluency in English /b (written and spoken). bSpanish /bis much recommended /li /ul pbHighly Valued Skills /b /pulliExperience in data-driven models (Machine Learning / AI) applied to battery systems /liliKnowledge of hybrid modelling approaches (physics-based + machine learning) or physics-informed models /liliExperience deploying models on embedded systems or edge devices (e.g., microcontrollers, TensorFlow Lite) /liliExperience in battery characterization /liliFamiliarity in Digital Twin concepts and IoT platforms /liliExperience in redox flow batteries or alternative chemistries beyond lithium-ion /liliPrevious involvement in European or national RD collaborative projects /li /ul pbWhat We Offer /b /pulliOpportunity to work on state-of-the-art battery modelling bridging research and industrial deployment /liliExposure to the full technological stack, from electrochemistry to AI models and edge/cloud integration /liliParticipation in high-impact European innovation projects /liliA collaborative and multidisciplinary working environment /liliFlexible working conditions, including hybrid work arrangements /li /ul pbAbout NVISION / Smart Battery Unit /b /ppNVISION brings advanced RD in IoT, Artificial Intelligence, and energy systems into real-world applications. Within the Smart Battery Unit, we focus on next-generation battery intelligence by combining physics-based modelling, AI, and digital platforms to enhance battery performance, safety, and lifetime across mobility and stationary applications /ppbr/ppWe're looking for someone at +/-2h timezone from Barcelona (Spain, CET), for the sake of coordination and synergies with the team. NVISION will not provide VISA sponsorship as a general rule, but if the candidate is enough qualified it will be considered as an exception /p