Overview

Undergraduate Student - Computational Earth Sciences (R0) at the Barcelona Supercomputing Center (BSC-CNS).

Closing Date: Friday, 17 October, ****.

Responsibilities

Develop and maintain open-source repositories containing data processing pipelines, machine learning training scripts, and model evaluation tools related to climate prediction and extreme event attribution.

Contribute to the design and implementation of reproducible data workflows, ensuring transparency and usability for the broader climate science community.

Collaborate with climate scientists and machine learning experts to integrate models and datasets into the platform, and adapt tools to different use cases and research needs.

Document pretrained models, benchmark datasets, and evaluation protocols, making them accessible and easy to use by external researchers.

Support the deployment and maintenance of the Open Science Platform, including version control, continuous integration, and basic platform testing.

Participate in meetings and collaborative efforts within the EXPECT consortium and with external users to gather feedback and improve the platform\'s usability and scientific value.

Contribute to outreach and training materials, such as tutorials and example notebooks, to support the adoption of the platform by the climate research community.

Qualifications

Education

Enrolled in a Bachelor\'s or Master's program in Computer Science, Math, Data Science, Environmental Sciences, or a related field.

Essential Knowledge And Professional Experience

Strong programming skills in Python and familiarity with machine learning libraries such as PyTorch, TensorFlow, or Scikit-learn.

Experience in handling, analyzing, and validating large datasets.

Experience in developing and training machine learning models.

Familiarity with working in a UNIX-based computational environment.

Additional Knowledge And Professional Experience

Experience working with climate, weather and earth datasets formats (netcdf, zarr,...).

Working knowledge of High-performance computing (HPC).

Experience with GPU-accelerated machine learning frameworks such as RAPIDS.

Competences

Strong problem-solving and analytical skills.

Ability to work independently and proactively in a research environment.

Effective communication and teamwork skills.

Proficiency in written and spoken English.

Conditions}

The position will be located at BSC within the Earth Sciences 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: competitive salary commensurate with qualifications and experience, in line with the cost of living in Barcelona.

Starting date: 01/10/2025.

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.

For more information contact ******.

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.

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