Researcher Job in Precision Agriculture for Field Crops at IRTA, Spain

The Institute of Agrifood Research and Technology (IRTA) is seeking an enthusiastic and motivated Researcher in Precision Agriculture for Field Crops to join the Sustainable Field Crops Program in Lleida, Catalonia, Spain. The position is aimed at an experienced researcher with a PhD in Agronomy, Precision Agriculture, Remote Sensing, Agricultural Engineering, Crop Science, or a related discipline.

IRTA is an agri-food research institute under the Government of Catalonia, with more than 1,000 professionals working across 19 research areas. The institute offers a dynamic and collaborative environment focused on scientific innovation, professional development, and practical solutions for agriculture and food systems.

The successful candidate will work at the intersection of precision agriculture, remote sensing, geospatial technologies, artificial intelligence, crop science, and digital agronomy. The research will focus on major arable crops such as rice, maize, wheat, and soybean, among others, through the Agrolabs Digitals IRTA initiative.

By combining field observations, satellite imagery, UAV and drone data, proximal sensors, GIS, agronomic knowledge, and data-driven technologies, the researcher will help develop practical decision-making tools for farmers and agricultural stakeholders. The overall objective is to support more resilient, productive, sustainable, and resource-efficient farming systems.

Key Details

Category	Details
Position	Researcher in Precision Agriculture for Field Crops
Host organization	IRTA – Institute of Agrifood Research and Technology
Research program	Sustainable Field Crops Program
Location	Lleida, Catalonia, Spain
Main research areas	Precision agriculture, remote sensing, digital agronomy, AI and GIS
Crops	Rice, maize, wheat, soybean and other arable crops
Required degree	PhD in Agronomy, Precision Agriculture, Agricultural Engineering, Crop Science or related field
Contract	Permanent or IRTA Consolida tenure-track position
Salary	Determined according to qualifications and experience
Expected start	October–November 2026, approximately
Working week	37.5 hours
Remote work	6 working days per month
International applicants	Eligible with immigration support

About the Precision Agriculture Research Position

This position focuses on using digital technologies to transform the way agricultural systems are monitored and managed. The researcher will develop approaches that connect remote sensing and geospatial information with agronomic knowledge, creating tools that can help farmers make better decisions about crops and inputs.

The work will cover a range of digital data sources, including satellite imagery, UAV and drone observations, proximal sensors, soil measurements, crop observations, weather information, and other in-field monitoring technologies.

A key objective will be to convert these diverse datasets into useful agronomic indicators, such as crop phenology, biomass, crop stress, and nutrient status. These indicators can then support crop monitoring, predictive modelling, and decision support.

The position also has a strong practical component. Rather than focusing exclusively on research outputs, the successful candidate will help translate scientific findings into scalable digital tools that can be used by farmers, advisors, agronomists, and other agricultural stakeholders.

Remote Sensing and Digitalization of Agricultural Systems

The researcher will design, implement, and improve methodologies for the digitalization of agricultural plots using multiple remote sensing technologies. This includes working with satellite imagery, UAV and drone data, proximal sensing systems, and in-field monitoring. The candidate will develop workflows capable of extracting meaningful information about crop development and field variability from these different sources.

Agronomic indicators derived from multi-source data may include crop phenology, biomass, stress levels, and nutrient status. The researcher will contribute to integrating these indicators into decision support systems (DSS) designed for arable crops. The ability to connect geospatial data with agronomic interpretation will be particularly important. The goal is to transform large and complex datasets into information that can support timely and practical crop-management decisions.

Data Management, AI and Machine Learning

A significant part of the position involves managing and integrating large agricultural datasets. The researcher will lead activities related to the cleaning, harmonization, structuring, processing, and integration of agronomic and environmental data. The successful candidate will develop reproducible data pipelines for data ingestion, processing, and storage. These pipelines should be compatible with digital platforms and decision support systems and should support reliable and repeatable research workflows.

Advanced analytics, artificial intelligence, and machine learning will be applied to identify patterns, develop predictive models, and improve decision support. The role therefore combines agricultural expertise with computational and data-science capabilities. Strong experience with programming environments such as R or Python will be valuable, particularly for handling complex datasets and developing analytical workflows.

Development of Decision Support Systems

The researcher will participate in the development and improvement of decision support systems for field crops. Examples include systems supporting crop variety selection in extensive crops and digital tools for recommending innovative crop-production technologies. The successful candidate will help translate experimental findings and agronomic knowledge into operational algorithms and recommendation systems.

These tools may include prescription maps, input-optimization systems, and other digital decision-making applications. The researcher will also help ensure that the tools are user-oriented, scalable, and adaptable to real-world farmer requirements. This practical focus makes the position relevant to researchers interested not only in academic research but also in the development and adoption of agricultural technologies.

Precision Agriculture and Input Optimization

A major research objective will be improving the efficiency with which agricultural inputs are used. The researcher will develop and validate site-specific management strategies for fertilizers, pesticides, water, and other inputs. Remote sensing data and predictive models will be integrated to identify spatial and temporal variability within fields and determine where inputs can be optimized without compromising productivity.

The researcher will contribute to the design of variable-rate application strategies and other precision-agriculture approaches that can improve input-use efficiency and support more sustainable crop production. The position therefore combines digital technologies with practical agronomy, with an emphasis on measurable improvements in productivity, resource efficiency, and environmental performance.

Field Trials and Demonstration Activities

The successful candidate will establish and manage short- and long-term field trials to test and validate precision-agriculture technologies and practices. Trials may involve important crops such as rice, wheat, maize, and soybean and may include AI-powered agricultural technologies. Field experiments will be used to assess whether digital tools and precision-management strategies deliver measurable benefits under practical production conditions.

An important responsibility will be demonstrating reductions in input use and improvements in application efficiency to farmers, stakeholders, and the scientific community. The researcher will therefore need to combine experimental skills with the ability to communicate results clearly and demonstrate the practical value of precision agriculture.

Collaboration and Knowledge Transfer

The position involves extensive collaboration with agronomists, farmers, industry partners, researchers, advisors, and other agricultural stakeholders.The researcher will help translate scientific results into practical and scalable applications. This includes providing training, organizing workshops, and offering technical support related to digital tools and precision-agriculture technologies.

Knowledge transfer will be an important part of the role, particularly in supporting the adoption of digital agriculture within the agricultural sector. The ability to understand end-user requirements and communicate effectively with both technical and non-technical audiences will therefore be valuable.

Scientific Reporting and Dissemination

The researcher will prepare high-quality research reports, peer-reviewed scientific publications, conference presentations, and materials for public audiences. The role also includes contributing to the communication of the economic and environmental benefits of precision agriculture. Particular emphasis will be placed on AI innovations and their potential impact on agricultural production and resource management. A strong scientific publication record and experience presenting research at conferences are among the required qualifications.

Grant Writing and Research Funding

The successful candidate will lead and contribute to the preparation of competitive research proposals and funding applications. Grant development will focus on areas such as sustainable agriculture, agricultural input efficiency, digital agronomy, precision farming, and AI integration in crop production. Experience in securing research funding and developing project proposals will therefore be important for candidates seeking to take a leadership role within the research program.

Mentorship and Research Leadership

The position includes responsibility for providing guidance and mentorship to junior researchers, interns, and technical staff. The researcher will contribute to creating a collaborative, innovative, and high-performing environment focused on the development and application of advanced AI and digital technologies in agriculture. Candidates should therefore demonstrate not only technical expertise but also the ability to support colleagues, coordinate activities, share knowledge, and contribute to team development.

Required Qualifications and Experience

Applicants must hold a PhD in Agronomy, Crop Science, Precision Agriculture, Agricultural Engineering, or a related field. Candidates should have proven experience in precision agriculture and digital agronomy, particularly in arable crops. Experience using remote sensing and field observations to monitor crops and support input optimization, including variable-rate technology, is required.

Strong expertise in remote sensing and geospatial analysis is also expected. This includes experience with satellite imagery, UAV or drone data, proximal sensing, and GIS technologies applied to agricultural systems. Candidates should understand the digitalization of agricultural systems and have experience integrating multi-source datasets, including soil, crop, and weather information, to generate useful agronomic indicators.

Experience in data management and processing using R, Python, or similar tools is required. Candidates should be comfortable cleaning, harmonizing, structuring, and integrating datasets for digital platforms or decision support systems. The position also requires experience with technologies used to map within-field soil variability, including tools such as bulk electrical conductivity and gamma-ray sensing.

A strong understanding of agronomic practices, crop physiology, and soil science is essential. Familiarity with integrated pest management and sustainable agricultural practices is also expected.

Candidates should have proven experience designing, implementing, and managing field trials and research projects, together with strong organizational skills and attention to detail. Experience working with multidisciplinary teams and diverse stakeholders, including farmers, advisors, agronomists, and industry partners, is required.

The successful candidate should also have strong communication and interpersonal skills, a solid record of peer-reviewed scientific publications and conference presentations, and experience developing project proposals and securing funding.

Experience mentoring junior researchers and interns is valued, as is a willingness to stay current with developments in precision-agriculture technologies and incorporate new approaches into research projects.

Strong analytical and problem-solving skills are required, together with the ability to turn complex agricultural challenges into practical solutions.

Proficiency in English is required. Candidates should also demonstrate strong teamwork skills, adaptability in multidisciplinary environments, and a commitment to professional growth and development.

Desirable Qualifications

A full driving licence valid in Europe and willingness to travel are desirable. Good communication skills and a client-oriented approach will also be valued, particularly because the position involves collaboration with farmers, industry, advisors, and other end-users.

Experience developing empirical and mechanistic models can strengthen an application. Advanced proficiency in R, Python, or equivalent programming environments is also desirable, particularly when working with large and complex agricultural datasets.

Strong knowledge of AI and machine learning for data processing, predictive modelling, and agricultural or geospatial decision support will be an advantage.

Knowledge of Catalan and Spanish is also valued.

Contract and Employment Conditions

IRTA offers this position as either a permanent position or an IRTA Consolida tenure-track position, depending on the qualifications and experience of the selected candidate.

The salary will be determined according to the qualifications and experience of the successful candidate. The standard working week is 37.5 hours, with Friday afternoons off. An intensive work schedule is available from June 15 to September 15.

The benefits package includes 23 vacation days, three days for family and work conciliation, and 45 hours of personal days. Employees can also work remotely for six working days per month and benefit from flexible working hours.

IRTA provides continuous training and professional development opportunities, supporting researchers in building long-term scientific and technical careers.

International Applicants

International candidates are welcome to apply. If the selected researcher is from a country outside the European Union, IRTA’s People Department will provide support with the process of obtaining the necessary residence and work permits.

Why Apply for This Precision Agriculture Research Position?

This position offers an opportunity to work at the intersection of agronomy, artificial intelligence, remote sensing, GIS, machine learning, and sustainable crop production.

The research has a strong applied focus. The successful candidate will not simply generate datasets or develop theoretical models but will help turn agricultural data into decision-making tools that can be tested and used under real farming conditions.

Working across crops such as rice, maize, wheat, and soybean also provides exposure to a diverse range of arable production systems. The combination of satellite and drone observations, proximal sensing, field experiments, soil variability mapping, AI, predictive modelling, and decision support creates a broad technical research portfolio.

For experienced researchers interested in digital agriculture, precision farming, agricultural AI, remote sensing, or sustainable intensification, this role offers an opportunity to contribute to both scientific research and technology transfer.

How to Apply

Candidates who meet the requirements and wish to be considered should submit their application through the online form APPLY NOW.

Applicants should ensure that their CV clearly demonstrates their PhD qualification, precision-agriculture experience, remote sensing and GIS expertise, programming and data-analysis skills, publication record, research funding experience, field-trial experience, and collaboration with farmers or industry where applicable. Candidates should also highlight experience with AI, machine learning, crop modelling, decision support systems, variable-rate technologies, or agricultural digitalization where relevant.

Frequently Asked Questions

What is the Researcher in Precision Agriculture position about?

The position focuses on using remote sensing, GIS, AI, machine learning, field data, and agronomic knowledge to develop digital tools for monitoring and managing arable crops.

Where is the position located?

The researcher will be based in Lleida, Catalonia, Spain, as part of IRTA’s Sustainable Field Crops Program.

What crops will the researcher work with?

The research may involve major arable crops including rice, maize, wheat, and soybean, among others.

What degree is required?

Applicants must have a PhD in Agronomy, Crop Science, Precision Agriculture, Agricultural Engineering, or a related discipline.

Is remote sensing experience required?

Yes. Proven expertise in remote sensing and geospatial analysis, including satellite imagery, UAV/drone data, proximal sensing, and GIS tools for agricultural applications, is required.

Is programming experience required?

Yes. Experience with R, Python, or similar programming and data-processing tools is required. Advanced programming and experience handling large datasets are desirable.

Is AI experience required?

The position involves applying AI and machine learning to agricultural data processing, predictive modelling, pattern detection, and decision support. Strong AI and machine-learning expertise is listed as a desirable qualification.

What are the employment conditions?

The position may be offered as a permanent position or an IRTA Consolida tenure-track position, depending on the selected candidate’s qualifications and experience.

What is the salary?

The salary will be determined according to the qualifications and experience of the selected candidate.

Does the position include remote work?

Yes. The employment conditions include six remote-working days per month, along with a flexible schedule.

Is fieldwork part of the position?

Yes. The researcher will establish and manage short- and long-term field trials to validate precision-agriculture technologies and practices across important arable crops.

Is experience with farmers and industry important?

Yes. The position involves collaboration with farmers, agronomists, advisors, industry partners, and other research teams, as well as training and knowledge-transfer activities.

Can international researchers apply?

Yes. Candidates from outside the European Union can apply. IRTA will provide support with residence and work permits for successful international candidates.

Are Catalan and Spanish required?

Catalan and Spanish are valued, while proficiency in English is specifically required.

When is the expected start date?

The anticipated start date is October–November 2026, approximately.