PhD Candidate in computer vision and image processing tecnologies focused on fruit crops

Universitat Autònoma de Barcelona; Bellaterra; Presencial; EUR 23.000 - 26.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Four-year contract

Doctoral grant up to €7,000

Descripción de la vacante

Universitat Autònoma de Barcelona in Bellaterra (Barcelona) and Lleida hosts a PhD project on computer vision and multispectral imaging for apple and peach crops. The candidate will co-supervise with IRTA and CVC, focusing on 3D reconstruction, detection, and segmentation in field conditions.

The program emphasizes digitalization of orchards and knowledge transfer to agriculture, with opportunities for training and professional growth within a European-level environment.

Formación

• University degree and master's in computer, data, industrial, electronic, or telecommunication engineering (or related fields).
• Proficiency in Python and data science/computer vision frameworks (e.g., PyTorch, TensorFlow, OpenCV, Pandas).
• Familiarity with Linux environments, databases, and version control systems (Git).
• Willingness to undertake fieldwork and data collection.
• Proficiency in English.
• Languages (Catalan and Spanish).
• Experience in precision agriculture or horticulture is beneficial.

Responsabilidades

• Collaborate on the design, set-up, and execution of experiments within the PhD project.
• Acquire images under field conditions and identify tree structures in orchards.
• Develop and validate AI and computer vision algorithms to detect flowers and fruits.
• Write scientific articles for publication in international venues and project reports.

Conocimientos

Python & CV frameworks

Fieldwork willingness

English proficiency

Educación

Master's degree in engineering or related field

Bachelor's degree in engineering

Herramientas

Linux

Git

Databases

Descripción del empleo

PhD Candidate in computer vision and image processing technologies focused on fruit crops

We are looking for a PhD Candidate in computer vision and image processing technologies focused on fruit crops to join the IRTA Fruit Production program based in Lleida and the Computer Vision Center (CVC) of the Autonomous University of Barcelona (UAB), based in Bellaterra (Barcelona). We offer the opportunity to be part of an organization with a dynamic, collaborative work environment focused on professional development.

The selected candidate will be able to choose their primary work location, either Bellaterra or Lleida, according to their preference. The position involves temporary mobility to Lleida and Girona for periods of several days throughout the year.

The selected candidate will develop a PhD project within a national research project funded by the Spanish State Research Agency (AEI) and join our research team and work on cutting-edge computer vision and image processing technologies focused on apple and peach crops under field conditions. The successful applicant will focus on developing advanced algorithms for 3D image reconstruction, object detection, and semantic segmentation. Additionally, the research will involve processing and analyzing multispectral imagery to solve complex real-world challenges. These solutions will support agronomic decision-making and site-specific crop management, actively contributing to the digitalization of orchards and technology transfer to the agricultural sector.

The successful applicant will be co-supervised by the Fruit Production Program at IRTA, which focuses on enhancing orchard competitiveness and sustainability against climate change through digital tools and efficient resource management, and the CVC at the UAB, a leading center dedicated to cutting-edge research in computer vision and artificial intelligence to tackle complex technological and industrial challenges. This research project will be carried out within the framework of the PhD Program in Computer Science at the UAB ( https://www.uab.cat/en/phds/computer-science ), specifically aligned with the computational models for artificial vision research line. This joint collaboration between IRTA and CVC within the UAB framework ensures an excellent, top European-level environment to train the candidate in cutting-edge technologies and promote successful knowledge transfer to the agricultural sector.

Tasks and Responsibilities:

• Collaborate on the design, set-up, and execution of experiments within the framework of the PhD research project. This includes contributing to study protocols alongside research staff and working within multidisciplinary teams (computer vision engineers and agronomists) to transform data into practical knowledge for the fruit-growing sector.
• Acquire images under field conditions and identify various tree structures—such as shoots, flowers at different phenological stages, fruitlets, and fruits—in apple and peach orchards.
• Perform advanced data and statistical analyses, curate datasets, and develop and validate AI and computer vision algorithms to detect and classify flowers, fruits, and other agronomically relevant elements under real orchard conditions.
• Conduct literature reviews and write scientific articles for publication in international peer-reviewed journals, conference proceedings, and project reports.

Required qualifications and experience

• Education: University degree and master's in computer, data, industrial, electronic, or telecommunication engineering (or related fields).
• Technical Skills: Proficiency in Python and data science/computer vision frameworks (e.g., PyTorch, TensorFlow, OpenCV, Pandas) applied to machine learning, deep learning, and image processing.
• Tools & Systems: Familiarity with Linux environments, databases, and version control systems (Git).
• Fieldwork & Mobility: Willingness to undertake fieldwork and data collection.
• Soft Skills: Strong teamwork and communication skills, ability to adapt to multidisciplinary environments, and a clear focus on professional growth and development.
• Applicants must not already hold a doctoral degree (PhD)
• Proficiency in English
• Additional and/or higher education in agronomy
• Experience in precision agriculture
• Knowledge of horticulture
• Languages (Catalan and Spanish)
• A valid Category B driving licence

Advantages of joining our team:

• Contract: 4 years
• First, second and third year of contract: 23.322,09€ gross per year
• Fourth year of contract: 26.325,47€ gross per year

*Subject to the corresponding withholdings, pursuant to prevailing regulations, and to the collective employment agreement of IRTA

The doctoral grant provides up to 7.000€ in additional funding to cover:

• Research stays of at least one month at other R&D centres.
• Tuition fees for the four years of the PhD programme.
• 37.5 hour workweek, with Friday afternoons off
• Intensive work schedule from 15/06 to 15/09
• 3 days of family & work conciliation
• 45 hours of personal days
• Flexible Schedule for a good work-life balance.
• Continuous training and professional growth opportunities.

Selected candidates must, at the time of signing the employment contract, provide documentation confirming either their admission to a doctoral programme or their enrolment in the programme.

Please know that if you are the chosen candidate and you are from a country which does not belong to the UE, IRTA's People Department will support you to get the residence and working permits.

Timings in the Recruitment Process

Curricular assessment: The candidate’s qualifications and merits will be evaluated according to the criteria established in the job offer.

Interview(s): These will be conducted by a Selection Committee to assess the candidate’s suitability in terms of professional experience and competencies.

Additional tests (if applicable): Depending on the position profile and the needs of the process, specific competency-based tests and/or a psychometric test may be included in order to more accurately assess the suitability of the candidates.
Start of contract: January 2027 (approximately)

The contract is part of project PID2025-170494OR-I00, funded by MICIU/AEI/10.13039/501100011033 and by the European Social Fund Plus FSE+.