PostDoc position

Universitat Autònoma de Barcelona; Bellaterra; On-site; EUR 28,000 - 34,000; Full time

Benefits offered by this job

GPU servers

Job summary

The Computer Vision Center (CVC) at the Campus of the Universitat Autònoma de Barcelona seeks a computer vision researcher to advance AI in agriculture under the AgriScienceFM Horizon Europe project. You will handle multimodal data pipelines and develop foundation models tailored for agricultural tasks.

The role combines cutting-edge research with practical evaluation across crop type mapping, yield forecasting, and environmental embeddings, within a collaborative research environment.

Qualifications

• PhD in Computer Science, ML, Data Science or related field.
• Deep learning and computer vision experience.
• Knowledge of foundation models and multispectral image processing.
• Python and DL frameworks such as PyTorch, TensorFlow and Scikit-Learn.

Responsibilities

• Multimodal data processing: define preprocessing pipelines for foundation model development.
• Agri-environmental foundation model generation using diverse datasets.
• Foundation model assessment against crop and water monitoring benchmarks.

Skills

Deep learning

Computer vision

Analytical skills

Independent working

Communication skills

Education

PhD in Computer Science / ML / AI

Tools

Python

PyTorch

TensorFlow

Scikit-Learn

Job description

The Computer Vision Center (CVC) is a non‑profit research center established in 1995 by the Generalitat de Catalunya and the Universitat Autònoma de Barcelona (UAB). Its mission is to carry out cutting‑edge research that has the highest international impact in the field of computer vision. It also promotes the transference of knowledge to industry and society.

Computer vision is an exciting research area and an omnipresent technology, essentially empowering machines with the sense of vision. The CVC is a successful marriage between knowledge and innovation. In addition to our cutting‑edge scientific achievements, we have established lasting ties with industrial partners and created several spin‑off companies.

Research area or group: Multispectral Image Analysis and Understanding (MSIAU)

Context and mission:

The MSIAU group is seeking a computer vision researcher to collaborate on the AgriScienceFM project, a Horizon Europe initiative to advancing the use of Artificial Intelligence (AI) in agricultural research and innovation through a consortium of 11 research institutes and universities. The project is devoted to developing Foundation Models specific for Agriculture, and their application to different downstream tasks and use cases.

The work will require managing and processing vast datasets to train multimodal Foundation models, consisting of Earth observation, weather and soil information, combined with agriculture‑specific spatial and temporal masks (e.g., spatial crop allocation) and pretext tasks (e.g., phenology observations, or synthetic crop growth model outputs). The models generated will offer agriculture‑specific environmental embeddings for a variety of use cases and applications, from crop type classification to yield forecasting, protein content estimation, soil health and farm advisory.

The project is funded by the European Union under Horizon Europe Grant Agreement No. 101293777 ("AgriscienceFM: AI Foundation Models in Agricultural Sciences", Activity HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61 of the call HORIZON-CL4-2025-01).

Key Duties:

• Multimodal data processing: Define and implement standardized preprocessing pipelines and harmonizing mechanisms to prepare raw multimodal agricultural datasets for ingestion into the foundation model development pipeline
• Agri-environmental foundation model generation: Develop foundation models for agri-environmental data, trained on different types of co-located large‑scale remote sensing and weather data.
• Foundation model assessment: Evaluate foundation models against defined benchmark tasks for crop and water monitoring, such as crop type mapping, phenological monitoring, yield outlooks, and irrigation water needs estimation, among others.

Requirements:

• Education
• PhD in Computer Science, Machine Learning, Data Science, Artificial Intelligence, or related fields.
• Essential Knowledge and Professional Experience
• Previous experience in deep learning and computer vision
• Knowledge of foundation models and multispectral image processing
• Good programming skills using Python and deep learning frameworks such as PyTorch, Tensorflow and Scikit‑learn.
• Additional Knowledge and Professional Experience
• Professional experience in remote sensing and agriculture applications
• Programming skills using high‑performance computing environments
• Competences
• Fluency in English and good communication skills.
• Strong problem‑solving and analytical skills
• Ability to work independently while collaborating effectively in a research environment.
• Ability to take initiative, prioritize and work under set deadlines and pressure

Conditions:

• The position will be based at the Computer Vision Center (Campus of the Universitat Autònoma de Barcelona).
• We offer a full‑time contract (37.5 hours per week) linked to the duration of the project and its available budget.
• A cutting‑edge research environment with access to advanced computing pipelines and multiple proprietary GPU servers.
• Ongoing training in advanced data‑analysis techniques and fine‑tuning of Foundation Models, including the implementation of scientific articles and attendance at workshops and lectures.
• Gross salary: 31.211€ / year
• Starting date: as soon as possible

OTM‑R principles for selection processes

The CVC is committed to Open Transparent and Merit‑based Recruitment (OTM‑R) for any potential candidate in all our processes. In 2015 we received the Human Resources Strategy for Researchers (HRS4R) award.In October 2022, the CVC successfully completed the accreditation renewal process after an on‑site visit and evaluation by EU experts.

Through an extensive and continuous process, we improve the conditions and opportunities at CVC. With these actions, the CVC is committed to the principles of the European Charter for Researchers, as well as the Code of Conduct for the Recruitment of Researchers. For more information follow this link .