Azafato/a - Ponpox Azafatas SL - Tarragona

Job Title: Battery Modelling Researcher (Physics-Based & AI Models) Location: Barcelona, Spain Position Overview We are seeking a highly motivated and skilled researcher to join our Smart Battery Unit in Barcelona. The successful candidate will work at the intersection of electrochemical modelling, data-driven methodologies, and real-world battery systems This 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 R&D projects, while supporting the transition of innovative modelling approaches into scalable, production-ready solutions Key Responsibilities • Develop and implement physics-based battery models, with a strong focus on electrochemical modelling (e.g., P2D and reduced-order models), • Design, develop, and validate data-driven and hybrid models for State of Charge (SoC), State of Health (SoH), and Remaining Useful Life (RUL) estimation, • Work with and extend frameworks such as PyBaMM for simulation and model development, • Translate advanced models into deployable solutions for BMS, including embedded (edge) and cloud-based architectures, • Analyse experimental and real-world battery data for model calibration and validation, • Contribute to the development of Digital Twins for battery systems, • Collaborate with multidisciplinary teams across Artificial Intelligence (AI), Internet of Things (IoT), and hardware domains, • Support proposal preparation and technical development in European R&D projects (e.g., Horizon Europe) Required Profile • Strong background in battery modelling, including:, • Electrochemical models (essential), • Physics-based modelling approaches, • Proficiency in Python for scientific computing, • Hands-on experience with PyBaMM, • Solid understanding of battery systems and Battery Management Systems (BMS), • Experience working with experimental data and model validation, • Degree in Electrical Engineering, Chemical Engineering, Physics, or a related field (MSc or PhD preferred), • Fluency in English (written and spoken). Spanish is much recommended Highly Valued Skills • Experience in data-driven models (Machine Learning / AI) applied to battery systems, • Knowledge of hybrid modelling approaches (physics-based + machine learning) or physics-informed models, • Experience deploying models on embedded systems or edge devices (e.g., microcontrollers, TensorFlow Lite), • Experience in battery characterization, • Familiarity in Digital Twin concepts and IoT platforms, • Experience in redox flow batteries or alternative chemistries beyond lithium-ion, • Previous involvement in European or national R&D collaborative projects What We Offer • Opportunity to work on state-of-the-art battery modelling bridging research and industrial deployment, • Exposure to the full technological stack, from electrochemistry to AI models and edge/cloud integration, • Participation in high-impact European innovation projects, • A collaborative and multidisciplinary working environment, • Flexible working conditions, including hybrid work arrangements About NVISION / Smart Battery Unit NVISION brings advanced R&D 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 We'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

Job Title: Battery Modelling Researcher (Physics-Based & AI Models) Location: Barcelona, Spain Position Overview We are seeking a highly motivated and skilled researcher to join our Smart Battery Unit in Barcelona. The successful candidate will work at the intersection of electrochemical modelling, data-driven methodologies, and real-world battery systems This 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 R&D projects, while supporting the transition of innovative modelling approaches into scalable, production-ready solutions Key Responsibilities • Develop and implement physics-based battery models, with a strong focus on electrochemical modelling (e.g., P2D and reduced-order models), • Design, develop, and validate data-driven and hybrid models for State of Charge (SoC), State of Health (SoH), and Remaining Useful Life (RUL) estimation, • Work with and extend frameworks such as PyBaMM for simulation and model development, • Translate advanced models into deployable solutions for BMS, including embedded (edge) and cloud-based architectures, • Analyse experimental and real-world battery data for model calibration and validation, • Contribute to the development of Digital Twins for battery systems, • Collaborate with multidisciplinary teams across Artificial Intelligence (AI), Internet of Things (IoT), and hardware domains, • Support proposal preparation and technical development in European R&D projects (e.g., Horizon Europe) Required Profile • Strong background in battery modelling, including:, • Electrochemical models (essential), • Physics-based modelling approaches, • Proficiency in Python for scientific computing, • Hands-on experience with PyBaMM, • Solid understanding of battery systems and Battery Management Systems (BMS), • Experience working with experimental data and model validation, • Degree in Electrical Engineering, Chemical Engineering, Physics, or a related field (MSc or PhD preferred), • Fluency in English (written and spoken). Spanish is much recommended Highly Valued Skills • Experience in data-driven models (Machine Learning / AI) applied to battery systems, • Knowledge of hybrid modelling approaches (physics-based + machine learning) or physics-informed models, • Experience deploying models on embedded systems or edge devices (e.g., microcontrollers, TensorFlow Lite), • Experience in battery characterization, • Familiarity in Digital Twin concepts and IoT platforms, • Experience in redox flow batteries or alternative chemistries beyond lithium-ion, • Previous involvement in European or national R&D collaborative projects What We Offer • Opportunity to work on state-of-the-art battery modelling bridging research and industrial deployment, • Exposure to the full technological stack, from electrochemistry to AI models and edge/cloud integration, • Participation in high-impact European innovation projects, • A collaborative and multidisciplinary working environment, • Flexible working conditions, including hybrid work arrangements About NVISION / Smart Battery Unit NVISION brings advanced R&D 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 We'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

Job Title: Battery Modelling Researcher (Physics-Based & AI Models) Location: Barcelona, Spain Position Overview We are seeking a highly motivated and skilled researcher to join our Smart Battery Unit in Barcelona. The successful candidate will work at the intersection of electrochemical modelling, data-driven methodologies, and real-world battery systems This 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 R&D projects, while supporting the transition of innovative modelling approaches into scalable, production-ready solutions Key Responsibilities • Develop and implement physics-based battery models, with a strong focus on electrochemical modelling (e.g., P2D and reduced-order models), • Design, develop, and validate data-driven and hybrid models for State of Charge (SoC), State of Health (SoH), and Remaining Useful Life (RUL) estimation, • Work with and extend frameworks such as PyBaMM for simulation and model development, • Translate advanced models into deployable solutions for BMS, including embedded (edge) and cloud-based architectures, • Analyse experimental and real-world battery data for model calibration and validation, • Contribute to the development of Digital Twins for battery systems, • Collaborate with multidisciplinary teams across Artificial Intelligence (AI), Internet of Things (IoT), and hardware domains, • Support proposal preparation and technical development in European R&D projects (e.g., Horizon Europe) Required Profile • Strong background in battery modelling, including:, • Electrochemical models (essential), • Physics-based modelling approaches, • Proficiency in Python for scientific computing, • Hands-on experience with PyBaMM, • Solid understanding of battery systems and Battery Management Systems (BMS), • Experience working with experimental data and model validation, • Degree in Electrical Engineering, Chemical Engineering, Physics, or a related field (MSc or PhD preferred), • Fluency in English (written and spoken). Spanish is much recommended Highly Valued Skills • Experience in data-driven models (Machine Learning / AI) applied to battery systems, • Knowledge of hybrid modelling approaches (physics-based + machine learning) or physics-informed models, • Experience deploying models on embedded systems or edge devices (e.g., microcontrollers, TensorFlow Lite), • Experience in battery characterization, • Familiarity in Digital Twin concepts and IoT platforms, • Experience in redox flow batteries or alternative chemistries beyond lithium-ion, • Previous involvement in European or national R&D collaborative projects What We Offer • Opportunity to work on state-of-the-art battery modelling bridging research and industrial deployment, • Exposure to the full technological stack, from electrochemistry to AI models and edge/cloud integration, • Participation in high-impact European innovation projects, • A collaborative and multidisciplinary working environment, • Flexible working conditions, including hybrid work arrangements About NVISION / Smart Battery Unit NVISION brings advanced R&D 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 We'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

Neotalent Conclusion es una de las mayores especialistas del mercado ibérico en captación y gestión de talento informático y de ingeniería.Como parte del grupo neerlandés Conclusion, que se compone por un ecosistema de 25 empresas y 3.En Neotalent Conclusion, somos especialistas del talento.At

Desde FERCHAU necesitamos incorporar a nuestro equipo de proyectos un/a MODELADOR/A REVIT MEP para unirse a nuestro equipo de la Zona Norte y trabajar en Bilbao desarrollando modelos 3D detallados en proyectos de alto valor añadido de Construcción y Edificación. Funciones: • Modelado en Revit MEP de conductos, tuberías, bandejas de cables y equipos MEP., • Coordinación BIM. Trabajo Colaborativo manejando archivos centrales y subpoyectos en entornos compartidos (BIM360)., • Creación de Familias paramétricas de MEP., • Generación de documentación técnica cumpliendo con los estándares BIM: planos 2D, secciones, detalles etc. Requisitos: • Formación: CFGS ó Grado en Arquitectura, Ingeniería Civil, Técnicos Superiores en Edificación u Obra Civil o similar., • Experiencia en proyectos de plantas industriales, plantas de generacion de energía, grandes edificaciones, etc., • Experiencia con Revit, AutoCAD y Naviswork., • Idiomas: valorable nivel B2 de inglés., • Persona con iniciativa, capacidad de trabajo en equipo, capacidad de comunicación, planificación y organización. Ofrecemos contratación estable y plan de carrera individualizado. Si crees que reúnes los requisitos, quieres incorporarte en Empresa Multinacional alemana, líder en el sector industrial europeo con posibilidades reales de crecer profesionalmente en un proveedor de Servicios de Ingeniería de primer orden, estaremos encantados de recibir tu candidatura y que formes parte de nuestro equipo y de nuestro proyecto.

Strong personal brand with authentic communication. Experience with brand collaborations or campaign partnerships preferred.

Recopilación y estandarización de datos para optimizar elementos BIM.

Strong personal brand with authentic communication. Experience with brand collaborations or campaign partnerships preferred.