Research Engineer in Spatial Data (RE1)

Job Reference

831_24_CASE_DPPP_RE1

Position

Research Engineer in Spatial Data (RE1)

Fecha de cierre

Viernes, 03 Enero, 2025
Reference: 831_24_CASE_DPPP_RE1
Job title: Research Engineer in Spatial Data (RE1)

About BSC

The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, 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 EuroHPC 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 Barcelona Supercomputing Center's Urban Data Science research team is looking for a research engineer specialized in spatial data analysis and bicycle mobility.

Urban Data Science is where city and urban data are used with AI and machine learning methods to tackle the most complex socio-economical challenges: equity, climate resilience, and quality of life.

The candidate will work on data and models towards helping cities become climate-neutral in 2030, in particular through fostering the transition to sustainable transportation modes such as cycling. The candidate will collaborate with city officials in urban intervention projects, as well as with the rest of the team and group researchers.

The candidate will prepare and analyse geolocated data from multiple heterogeneous sources, and create models and analyses that use these data to answer questions posed by the researchers as well as administration officials and other collaborators.

The candidate will be embedded in the Data Analytics and Visualization Group, within the Computational Applications in Science and Engineering department (CASE); which works with industry and academia developing software and applications that leverage the power of High-Performance Computing to solve real problems of people.

Key Duties

  • Receive, ingest, prepare, and clean data from external stakeholders
  • Analyze the data and develop statistical models with focus on spatial features
  • Aid with the synthesis, lessons for policy and planning, and dissemination activities
  • Collaborate in preparing publications and research outputs, including co-authored academic articles, policy briefs, and community events

Requirements

  • Education
    • Master on Data Science, Applied Mathematics, or Computer Science
  • Essential Knowledge and Professional Experience
    • Experience with spatial data analysis methods
    • Experience on applied data science projects
    • Knowledge and experience on data related to urban cycling
  • Additional Knowledge and Professional Experience
    • Experience with Python geospatial analysis libraries (e.g. GeoPandas, Pysal, etc.)
    • Experience with geoanalysis platforms (e.g. QGIS, Carto, etc.)
    • Fluency in spoken and written English and Spanish.
  • Competences
    • Excellent communication skills, especially for producing documentation (reports, manuals, papers).

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, support to the 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: 1 enero 2025

Applications procedure and process

All applications must be made through BSC website and contain:

  • A full CV in English including contact details
  • A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered

    In accordance with the OTM-R principles, a gender-balanced recruitment panel is formed for every vacancy at the beginning of the process. After reviewing the content of the applications, the panel will start the interviews, with at least one technical and one administrative interview. A profile questionnaire as well as a technical exercise may be required during the process.

    The panel will make a final decision and all candidates who had contacts with them will receive a feedback with details on the acceptance or rejection of their profile.

    At BSC we are seeking continuous improvement in our recruitment processes, for any suggestions or feedback/complaints about our Recruitment Processes, please contact recruitment [at] bsc [dot] es.

    For more information 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

    Application Form

    please choose one of this and if needed describe the option : - BSC Website - Euraxess - Spotify - HiPeac - LinkedIn - Networking/Referral: include who and how - Events (Forum, career fairs): include who and how - Through University: include the university name - Specialized website (Metjobs, BIB, other): include which one - Other social Networks: (Twitter, Facebook, Instagram, Youtube): include which one - Other (Glassdoor, ResearchGate, job search website and other cases): include which one
    Please, upload your CV document using the following name structure: Name_Surname_CV
    Los archivos deben ser menores que 3 MB.
    Tipos de archivo permitidos: txt rtf pdf doc docx.
    Please, upload your CV document using the following name structure: Name_Surname_CoverLetter
    Los archivos deben ser menores que 3 MB.
    Tipos de archivo permitidos: txt rtf pdf doc docx zip.
    Please, upload your CV document using the following name structure: Name_Surname_OtherDocument
    Los archivos deben ser menores que 10 MB.
    Tipos de archivo permitidos: txt rtf pdf doc docx rar tar zip.
    ** Consider that the information provided in relation to gender and nationality will be used solely for statistical purposes.