Researcher in Precision Agriculture for Field Crops
4 days ago
Lleida
ppWe are looking for a enthusiastic and motivated bResearcher /b with a PhD in Agronomy, Precision Agriculture, Remote Sensing, or a related field to join the bSustainable Field Crops Program /b team, based in bLleida /b. We offer the opportunity to be part of an organization with a dynamic, collaborative work environment focused on professional development. /ph3Tasks and Responsibilities: /h3h3Remote Sensing and Digitalization of Agricultural Systems: /h3olliDesign, implement and improve methodologies for the digitalization of agricultural plots using remote sensing technologies, including satellite imagery, UAV/drone data, proximal sensors and in-field monitoring systems. /liliDevelop workflows to extract agronomic indicators (e.g., crop phenology, biomass, stress, nutrient status) from multi-source data. /liliContribute to the integration of these datasets into decision support systems (DSS) for arable crops. /li /olh3Data Management, Processing and Integration: /h3olliLead the cleaning, harmonization, and structuring of agronomic and environmental datasets related to crop development. /liliBuild reproducible pipelines for data ingestion, processing, and storage, ensuring compatibility with digital platforms and DSS tools. /liliApply advanced analytics, AI and machine learning techniques for pattern detection, predictive modelling and decision support. /li /olh3Development of Decision Support Tools (DSS): /h3olliParticipate in the development and improvement of DSS like a DSS for crop variety selection in extensive crops or digital tools for recommending innovative crop production technologies. /liliTranslate agronomic knowledge and experimental results into operational algorithms and recommendation systems (e.g., prescription maps, input optimization tools). /liliEnsure tools are user-oriented, scalable and adaptable to farmer needs. /li /olh3Precision Agriculture and Input Optimization: /h3olliDevelop and validate strategies for site-specific management of inputs (fertilizers, pesticides, water) using precision agriculture approaches. /liliIntegrate remote sensing data and predictive models to optimize input use efficiency while maintaining productivity. /liliContribute to the design of variable-rate application strategies and sustainability-oriented practices. /li /olh3Field Trials and Demonstrations: /h3olliSet up and manage short- and long-term field trials to test and validate precision agriculture technologies and practices — including AI-powered solutions — across key crops (e.g., rice, wheat, maize, and soybeans). /liliProof measurable benefits of reduced input usage and improved application efficiency to farmers, stakeholders and the scientific community. /li /olh3Collaboration and Knowledge Transfer: /h3olliWork closely with agronomists, farmers, industry partners and other research teams to translate findings into practical, scalable applications. /liliProvide training, workshops and technical support focused on the transfer of knowledge on digital tools to end-users and the adoption of precision agriculture and digital technologies in the sector. /li /olh3Reporting and Dissemination: /h3olliProvide high-quality reports, peer-reviewed scientific publications, and presentations for journals, conferences and public audiences. /liliContribute to the dissemination of the economic and environmental benefits of precision agriculture, with particular emphasis on AI innovations and their impact. /li /olh3Grant Writing and Funding: /h3ulliLead and contribute to the development of competitive grant proposals and funding applications to secure resources in sustainable agriculture, input efficiency and AI integration in crop production. /li /ulh3Mentorship and Leadership: /h3ulliProvide guidance and mentorship to junior researchers, interns and technical staff, fostering a collaborative, innovative and high-performance environment centered on cutting‑edge AI applications in agriculture. /li /ulh3Required qualifications and experience /h3ulliPh.D. in Agronomy, Crop Science, Precision Agriculture, Agricultural Engineering, or a related field. /liliProven experience in precision agriculture and digital agronomy, particularly in arable crops, including the use of remote sensing data and field observations to support input optimization (e.g. variable‑rate technology) and crop monitoring. /liliExpertise in remote sensing and geospatial analysis, including the use of satellite imagery, UAV/drone data, proximal sensing and GIS tools for agricultural applications. /liliExperience in the digitalization of agricultural systems, including integration of multi‑source data (soil, crop, weather) and generation of agronomic indicators. /liliDemonstrated experience in data management and processing (e.g., R, Python, or similar), including cleaning, harmonization, structuring, and integration of datasets for use in decision support systems (DSS) or digital platforms. /liliExperience in the use of different technologies (bulk electric conductivity, gamma rays, etc.) to map soil field intra‑field variability. /liliDeep understanding of agronomic practices, crop physiology and soil science. Familiarity with integrated pest management (IPM) and sustainable agriculture practices. /liliProven ability to design, implement, and manage field trials and research projects. Strong organizational skills and attention to detail. /liliExperience working in multidisciplinary teams and with diverse stakeholders, including farmers, advisors, agronomists and industry partners. /liliStrong communication and interpersonal skills. /liliA strong track record of publishing research findings in peer‑reviewed scientific journals and presenting at conferences. /liliExperience in developing project proposals and securing funding. /liliAbility to mentor and guide junior researchers and interns, fostering a collaborative and innovative environment. /liliWillingness to stay updated with advancements in precision agriculture technologies and integrate new approaches into projects. /liliStrong analytical and problem‑solving skills, with the ability to develop practical solutions to complex agricultural challenges. /liliProficiency in English. /liliStrong teamwork skills, ability to adapt to multidisciplinary environments and a focus on professional growth and development. /li /ulh3Desirable requirements /h3ulliFull driving license for Europe and travelling availability. /liliGood communication skills and client‑oriented thinking and working. /liliExpertise in methodological approaches to develop empirical and mechanistic models. /liliAdvanced proficiency in data analysis and programming environments, such as R, Python, or equivalent, including experience in handling large and complex datasets. /liliStrong capability in the use of AI and machine learning techniques for data processing, predictive modelling and decision support in agricultural or geospatial contexts. /liliCatalan and Spanish are valued. /li /ulh3Advantages of joining our team /h3ulliContract: permanent position or IRTA Consolida (tenure track) position subject to the qualifications and experience of the selected candidate. /liliSalary: to be resolved according to the qualifications and experience of the selected candidate. /lili37.5 hour workweek, with Friday afternoons off. /liliIntensive work schedule from 15/06 to 15/09. /lili23 vacation days. /lili3 days of family work conciliation. /lili45 hours of personal days. /liliRemote work 6 workdays per month. /liliFlexible Schedule for a good work‑life balance. /liliContinuous training and professional growth opportunities. /li /ulpEqual treatment and equal opportunities are guaranteed for all candidates in the selection process, avoiding stereotypes, bias or barriers linked to gender, sexual orientation, origin, age, ideology, or any other potentially discriminatory condition. The organization also ensures inclusion commitment toward vulnerable groups, and the first round of the selection process is reserved for candidates with functional diversity. /p /p #J-18808-Ljbffr