Spain Job Openings

Barcelona Supercomputing Center (BSC)

Researcher Digitalization of hydrogen-based energy systems for hydrogen production (R2) - AI4S

Barcelona

FULL TIME

September 13, 2024

Job Reference
630_24_CASE_PTG_R2
Position
Researcher Digitalization of hydrogen-based energy systems for hydrogen production (R2) - AI4S
Closing Date
Monday, 30 September, 2024
Reference: 630_24_CASE_PTG_R2
Job title: Researcher Digitalization of hydrogen-based energy systems for hydrogen production (R2) - AI4S


About BSC


The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for Euro HPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.

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We are particularly interested for this role in the strengths and lived experiences of women and underrepresented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under-represented sex will be favoured.

We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.

If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.


Context And Mission


The current needs for decarbonization have placed hydrogen and hydrogen-enriched fuels as an efficient solution for the transition to a clean, low-carbon energy system. Nonetheless, reducing the emissions and the carbon dependency to the levels of the EU targets brings new challenges to the energy-intensive industrial processes like steel manufacturing or power generation. The development of power-to-X (P2X) technologies can be used to produce hydrogen from renewable electricity referred as “green hydrogen” and supply the fuel demands of such processes reducing the carbon-foot print and the fossil fuel dependency of the process. Hydrogen-based technologies are identified to be key for the energy transition and demands digital tools and advanced software to accelerate the deployment of these technologies to the market. Within this context, the candidate will develop a research activity comprising the development of infrastructure for the generation of Digital Twins based on process data using Artificial Intelligence (AI) and physics-based reduced-order models.

Green hydrogen is generated from water and renewable electricity in an electrolyser. This renewable hydrogen can be stored and distributed for later use in highly efficient electrochemical systems such as fuel cells. The most efficient electrolyzers and fuel cells are based on Solid Oxide Cells (SOCs) operating at high temperatures. These novel technologies for electrolysis Solid Oxide Electrolysis (SOEs) involve multiple physical and chemical phenomena ranging from thermo-fluidics occurring at the cm-scale to electrochemistry taking place at the nanoscale. This multi-physics multi-scale complexity makes such devices extremely challenging from the simulation point of view while, at the same time, makes simulation outputs highly valuable to predict and design real operating systems.

The applicant will join the Propulsion Technologies Group (PTG), a research group from the Computer Applications in Science and Engineering (CASE) Department at the Barcelona Supercomputing Center. As part of the PTG, the applicant will join a multidisciplinary team with background in advanced computational models for high fidelity simulation of energy conversion systems. The PTG is actively involved in several European research-oriented for which results are disseminated in highly ranked scientific journals, and conferences, and industrial projects with focus on technology transfer to industry.

The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
For more information, please check: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s


Key Duties


  • Developing an efficient ML-based platform for training CNN from large scale datasets.
  • Developing reduced-order models for electrolizers and sub-components using data-driven methods.
  • Developing physics-based reduced-order models from simulation data.
  • Interact with the different academic and industrial partners to carry our collaborative research.
  • Contribute to scientific publications and reporting to different National and EU projects the researcher will be involved in.


Requirements


  • Education
    • The candidate should hold a Degree or Ph D in Chemistry, Physics, Mechanical Engineering, or Data analytics with background in computational science and Artificial Intelligence.
  • Essential Knowledge and Professional Experience
    • Solid background on data-driven methods
    • Fluid mechanics and Materials Science
    • General knowledge on data-driven methods, python programing and Machine Learning are expected.
    • General knowledge on computer science and programming languages such as Fortran, C, and C++
  • Additional Knowledge and Professional Experience
    • Fluency in English is essential. Proficiency in Spanish and other European languages would be advantageous.
    • Computational skills and parallel programming for HPC
  • Competences
    • Ability to work in a team and in a multi-cultural environment.
    • Strong analytical skills.
    • Ability to work independently and within a team.


Conditions


  • The position will be located at BSC within the CASE Department
  • We offer a full-time contract (37.5h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance
  • Duration: 4 years
  • Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
  • Salary: 45.00,00€
  • Additional Expenses Grant: Each fellowship will be associated with a grant for additional expenses, such as IT equipment, travel, training, stays, etc.
  • Starting date: asap - the incorporation for this vacancy must be before the 16th of December 2024


Applications procedure and process


All applications must be submitted via the BSC website and contain:
  • A full CV in English, including contact details.
  • A cover/motivation letter with a statement of interest in English, clearly specifying for which specific area and topics the applicant wishes to be considered. Additionally, two references for further contacts must be included. Applications without this document will not be considered.


Development of the recruitment process

The selection will be carried out through a competitive examination system ("Concurso-Oposición"). The recruitment process consists of two phases:
  • Curriculum Analysis: Evaluation of previous experience and/or scientific history, degree, training, and other professional information relevant to the position. - 40 points
  • Interview phase: The highest-rated candidates at the curriculum level will be invited to the interview phase, conducted by the corresponding department and Human Resources. In this phase, technical competencies, knowledge, skills, and professional experience related to the position, as well as the required personal competencies, will be evaluated. - 60 points. A minimum of 30 points out of 60 must be obtained to be eligible for the position.
The recruitment panel will be composed of at least three people, ensuring at least 25% representation of women.
In accordance with OTM-R principles, a gender-balanced recruitment panel is formed for each vacancy at the beginning of the process. After reviewing the content of the applications, the panel will begin the interviews, with at least one technical and one administrative interview. At a minimum, a personality questionnaire as well as a technical exercise will be conducted during the process.
The panel will make a final decision, and all individuals who participated in the interview phase will receive feedback with details on the acceptance or rejection of their profile.


At BSC, we seek continuous improvement in our recruitment processes. For any suggestions or comments/complaints about our recruitment processes, please contact recruitment [at] bsc [dot] es.

For more information, please follow this link.


Deadline


The vacancy will remain open until a suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.


OTM-R principles for selection processes


BSC-CNS is committed to the principles of the Code of Conduct for the Recruitment of Researchers of the European Commission and the Open, Transparent and Merit-based Recruitment principles (OTM-R). This is applied for any potential candidate in all our processes, for example by creating gender-balanced recruitment panels and recognizing career breaks etc.
BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.
For more information follow this link
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