Hpc And Ai/Ml-Driven Development And Optimization Of Atmospheric And Climate Models (R2) - Ai4S

Job Reference

566_24_ES_CES_R2

Position

HPC and AI/ML-Driven Development and Optimization of Atmospheric and Climate Models (R2) - AI4S

Closing Date

Thursday, 31 October, 2024
Reference: 566_24_ES_CES_R2
Job title: HPC and AI/ML-Driven Development and Optimization of Atmospheric and Climate Models (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.

Look at the BSC experience:
BSC-CNS You Tube Channel
Let's stay connected with BSC Folks!

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 successful candidate will join the Computational Earth Sciences group as a specialist in the development and optimisation of atmospheric and climate models. This role will focus on improving the performance and efficiency of our existing code base using High-Performance Computing (HPC) techniques and leading the refactoring process to ensure that our models are optimised for current and next-generation supercomputing architectures.

In addition, the candidate may explore and apply AI/ML methodologies to various components of the modelling workflow. This includes opportunities to innovate by integrating AI-driven solutions, such as model trajectory emulators or automated land use map generation, that can be used to improve the accuracy and efficiency of terrestrial climate prediction models.

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

"La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.
Para más información: https://www.bsc.es/join-us/excellence-career-opportunities/ai4s "
Key Duties

- Develop optimizations for existing atmospheric and climate models, focusing on improving performance on HPC systems.
- Collaborate with climate scientists and other researchers to integrate optimized and AI-enhanced models into system.
- Identify and implement AI/ML-driven solutions within the modelling workflow, such as land use mapping or other enhancements to improve model accuracy and efficiency.
- Document the development process, ensuring clear guidelines and support for the deployment and use of optimized models and AI-driven tools.

Requirements

- Education

- Bachelor's degree in Computer Science, Physics, or a related field.

- A Ph D in a relevant field is mandatory.

- Essential Knowledge and Professional Experience

- Strong experience in high-performance computing, particularly in optimising and refactoring complex code bases for scalability and efficiency.

- Proficient in Fortran programming, with experience in refactoring legacy code to improve performance on HPC systems.

- Experience in parallel programming and code optimisation for multi-core and GPU-based HPC architectures.

- Familiarity with climate and atmospheric models, with a focus on their application in large-scale simulations.

- Additional Knowledge and Professional Experience

- Demonstrated knowledge of Unix or Linux-based HPC systems, including system optimisation through application performance tuning, understanding application scaling characteristics, workflow management, job scheduling, user resource management and user troubleshooting.

- Experience of profiling and debugging tools commonly used in HPC environments (e.g. GDB, Valgrind, Paraver suite, Scalasca, ARM-DDT).

- Knowledge of AI/ML techniques and their application in scientific computing, with experience of integrating AI into existing workflows.

- Familiarity with tools and frameworks for AI/ML, such as Tensor Flow or Py Torch, and their application in scientific modelling.

- Strong writing skills for drafting and publishing academic journal articles, including experience in preparing technical content for peer-reviewed publications.

- Fluency in English.

- Competences

- Ability to work independently and effectively as part of a multidisciplinary team.

- Strong analytical and problem-solving skills, with attention to detail.

- Excellent communication skills, with the ability to articulate technical concepts to both scientists and developers.

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
- Duration: 4 years
- Holidays: 23 paid vacation days plus 24th and 31st of December per our collective agreement
- Salary: 45.000,00€
- 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