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Researcher - Data Analytics and Digital Twin Development of Industrial Furnaces
hace 1 mes
Context and Mission
The transition to a clean, low-carbon energy system is a pressing need, and hydrogen and hydrogen-enriched fuels are being explored as efficient solutions. However, reducing emissions to EU targets poses significant challenges to energy-intensive industrial processes like steel manufacturing and power generation. The development of power-to-X (P2X) technologies can produce hydrogen from renewable electricity, reducing carbon footprints and fossil fuel dependency. Within this context, the candidate will develop a research activity focused on creating infrastructure for Digital Twins based on process data using Artificial Intelligence (AI) and physics-based reduced-order models.
The Metallurgical Sector
The metallurgical sector, with its high dependency on fossil fuels, could greatly benefit from clean combustion technologies and the use of cleaner, more sustainable fuels. Hydrogen and hydrogen-enriched fuels have significant potential to enable the transition to a clean, low-carbon energy system. Nonetheless, reducing emissions to EU targets brings new challenges to the metallurgical sector, responsible for a large portion of pollutant emissions in the industrial sector and with a high dependency on fossil fuel supply.
Key Duties
- Develop an efficient ML-based platform for digital models using large-scale datasets.
- Develop reduced-order models for the full furnace and sub-components using data-driven methods.
- Interact with project partners to carry out collaborative research.
- Contribute to scientific publications and reporting on national and EU projects.
Requirements
- Education
- The candidate should hold a degree or PhD in Chemistry, Physics, Mechanical Engineering, or Data Analytics.
- Essential Knowledge and Professional Experience
- General knowledge of data-driven methods, Python programming, and Machine Learning is expected.
- Background in computational science and Artificial Intelligence is required.
- Solid background in data-driven methods, fluid mechanics, and Materials Science will be positively evaluated.
- Additional Knowledge and Professional Experience
- General knowledge of computer science and programming languages such as Fortran, C, and C++ will be highly valued.
- Computational skills and parallel programming for HPC are not necessary but will be considered an asset.
- Competences
- Strong analytical skills.
- Ability to work independently and within a team.
- Good communication and teamwork skills to work in a multidisciplinary team.
- Fluency in English is essential, and Spanish is welcome.
Conditions
- The position will be located at the Barcelona Supercomputing Center within the CASE Department.
- We offer a full-time contract, a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, an extensive training plan, restaurant tickets, private health insurance, and support for relocation procedures.
- Duration: Open-ended contract due to technical and scientific activities linked to the project and budget duration.
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement.
- Salary: We offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona.
- Starting date: As soon as possible.
