Fully Funded PhD Position in Multimodal Foundation Models for Environmental Pollution Sciences – AI Institute, Barcelona Supercomputing Center (BSC), Spain (EVELYN Project)

The AI Institute at the Barcelona Supercomputing Center (BSC) is offering a PhD position to work on Multimodal Foundation Models for Environmental Pollution Sciences within the European project EVELYN. This is an excellent opportunity for a highly motivated candidate interested in large-scale AI, multimodal learning, environmental data science, and high-performance computing (HPC).

Position Snapshot

• Institution: Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC), AI Institute, Barcelona, Spain

• Project: EVELYN – Multimodal Foundation Models for Environmental Pollution Sciences

• Level: PhD / Doctoral Researcher

• Department: AI Institute (in collaboration with Earth Sciences / other relevant departments, depending on supervision)

• Funding: Fully funded PhD position (full-time contract, 35 hours/week)

• Research areas:

  • Multimodal foundation models (e.g., language, vision, spatiotemporal and environmental data)

  • Large-scale machine learning and deep learning

  • Environmental pollution science and Earth/environmental data

  • High-performance computing (HPC) for large-scale model training

  • AI for scientific discovery and decision support in environmental applications

• Start date: As soon as possible / by mutual agreement

• Application deadline: [Check the BSC job page for the current closing date; the position is typically open until filled]

• Job reference: 397_26_AII_SRE2 (check on the BSC portal; if different, use the reference shown on the job page)

• Application portal: BSC job portal – https://www.bsc.es/join-us/job-opportunities/39726aiisre2

• Application fee: None

About the EVELYN Project

The EVELYN project is a European research initiative focusing on the development of Multimodal Foundation Models for environmental pollution sciences. The goal is to leverage large-scale, heterogeneous data from multiple modalities (e.g., satellite imagery, in-situ sensor data, climate reanalyses, emissions inventories, text reports, and other environmental datasets) to advance scientific understanding, prediction, and decision-making in environmental pollution.

The PhD candidate will work within the BSC AI Institute, in close collaboration with Earth Sciences and other multidisciplinary teams, to develop and apply multimodal AI models and foundation models tailored to environmental pollution problems. This includes the design of architectures and training strategies that can process and integrate diverse data sources, and the evaluation of these models in real-world environmental use cases.

Key research activities include:

• Designing, implementing, and training multimodal foundation models that integrate diverse environmental data modalities (e.g., images, time series, gridded data, text)

• Developing data preprocessing and representation pipelines for large-scale environmental pollution datasets

• Exploring and implementing scalable training strategies in HPC environments (e.g., distributed training, model parallelism)

• Evaluating model performance on environmental prediction, monitoring, and decision-support tasks (e.g., pollution forecasts, hotspot detection, attribution, scenario analysis)

• Contributing to scientific publications, project deliverables, and open-source software related to EVELYN

• Collaborating with project partners across Europe, including experts in AI, environmental science, and domain-specific applications

• Presenting research at international conferences and workshops

This project combines foundation models, multimodal AI, environmental science, and HPC to tackle some of the most pressing challenges in environmental pollution monitoring and mitigation.

Funding and Employment Conditions

Selected candidates will receive a fully funded PhD position with the following core features (as per typical BSC conditions for PhD roles):

• Contract type: Full-time employment (35 hours/week) located at BSC in Barcelona

• Duration: Multi-year contract aligned with the PhD duration and project funding (typically 3–4 years)

• Salary: Competitive salary commensurate with the candidate’s qualifications and experience, and according to the cost of living in Barcelona

• Benefits:

  • Highly stimulating research environment with access to state-of-the-art HPC infrastructure (e.g., MareNostrum supercomputer)

  • Flexible working hours

  • Extensive training and career development plan

  • Restaurant tickets

  • Private health insurance (for national and international staff)

  • Support for relocation procedures (visa, housing, etc.)

  • 22 days of annual leave + 6 personal days + 24th and 31st of December (as per BSC collective agreement)

The PhD position is fully funded within the framework of the EVELYN project and the AI Institute at BSC.

Who Should Apply

This position is ideal for candidates with a strong background in computer science, machine learning, applied mathematics, physics, or related fields, and a clear interest in multimodal AI, foundation models, and environmental applications.

Academic Background

Applicants should have (or be close to completing):

• A Master’s degree in one of the following or closely related fields:

  • Computer Science

  • Artificial Intelligence / Machine Learning

  • Data Science

  • Applied Mathematics

  • Physics / Earth Sciences with strong computational focus

  • Computational Engineering or related quantitative disciplines

Required Qualifications and Experience

While the exact list is specified on the job page, typical requirements include:

• Solid knowledge of machine learning and deep learning methods

• Experience with deep learning frameworks such as PyTorch and/or TensorFlow

• Strong programming skills in Python and familiarity with software development best practices (e.g., version control with Git)

• Interest or prior experience in working with multimodal data (e.g., images, time series, text, gridded environmental data)

• Ability to work in a Linux/HPC environment or willingness to learn

• Good communication skills in English (spoken and written)

• Ability to work both independently and as part of an interdisciplinary team

Preferred Qualifications and Experience

• Experience with large-scale model training or working in HPC clusters (e.g., distributed training, GPU computing)

• Experience in environmental data science, Earth system modelling, or climate / air quality data

• Background in foundation models, multimodal learning, or transformers

• Experience with open-source development and scientific software engineering

• Previous research experience (e.g., Master’s thesis, research assistantships, publications)

Application Materials

All applications must be submitted via the BSC website. Applications submitted by email will not be considered.

Required documents typically include:

• Full CV in English including contact details, education, research experience, technical skills, and any publications or relevant projects

• Cover / motivation letter in English describing:

  • Your background and research interests

  • Why you are interested in the EVELYN project and this PhD position

  • How your skills and experience align with multimodal foundation models and environmental pollution sciences

• Contact details of two referees who can be contacted for references (name, affiliation, email, and optionally phone)

All documents should be uploaded through the BSC job portal in the specified formats. Applications that do not include all required documents may not be considered.

How to Apply (Step-by-Step)

1. Review the official job posting

   • Visit the BSC job page: https://www.bsc.es/join-us/job-opportunities/39726aiisre2

   • Carefully read the full description, requirements, and conditions.

2. Prepare your documents

   • Update your CV to highlight relevant coursework, projects, and experience in AI/ML, multimodal data, and/or environmental science.

   • Write a tailored motivation letter that connects your background to multimodal foundation models and the EVELYN project, and explains why you want to pursue this PhD at BSC.

   • Identify two referees and confirm their willingness to provide references.

3. Submit your application through the BSC portal

   • Go to the BSC job portal and click “Apply” on the EVELYN PhD position page.

   • Complete the online form and upload your CV, motivation letter, and referee information.

   • Double-check all information and documents before submitting.

4. Monitor your email

   • BSC will review applications on a rolling basis and contact shortlisted candidates for interviews.

   • Make sure to monitor your email (including spam/junk folders) for any communication from BSC’s recruitment team.

Selection Process

The BSC selection process typically involves:

• Curriculum analysis: Evaluation of academic background, research experience, technical skills, and overall fit with the position

• Interviews: Shortlisted candidates are invited for one or more interviews (online or on-site) with the hosting research group and HR, focusing on technical competencies, motivation, and teamwork skills

• Final decision: The best-ranked candidate will receive a formal offer and instructions regarding contract, start date, and relocation (if applicable)

The vacancy generally remains open until a suitable candidate has been hired; applications are reviewed regularly.

Why This Opportunity Stands Out

This PhD position offers a rare combination of:

• Cutting-edge AI research on multimodal foundation models applied to real-world environmental pollution challenges

• Access to one of Europe’s leading supercomputing centres (BSC), with state-of-the-art HPC infrastructure and a strong AI research environment

• An opportunity to work at the interface of AI, environmental science, and HPC, contributing to a European project with high scientific and societal impact

• A fully funded PhD contract with competitive salary, excellent benefits, and strong support for training, development, and international collaboration

• A vibrant international research community in Barcelona, with a high quality of life and a rich scientific ecosystem

For candidates passionate about large-scale AI, multimodal learning, and environmental applications, this is an outstanding opportunity to pursue a high-impact PhD at the AI Institute of the Barcelona Supercomputing Center.

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