Overview
A fully funded PhD opportunity is available at the Centre for Cleantech and Biomass Resource Efficiency (CCBRE) at Agricultural University Plovdiv, Bulgaria. This position is part of an interdisciplinary research initiative aimed at developing AI-based methodologies for detecting microplastics in recycled organic fertilizers. The project is significant as it addresses the critical issue of soil contamination caused by microplastics, which poses a threat to sustainable agricultural practices.
Background & Relevance
The detection of microplastics in agricultural inputs is becoming increasingly important as the presence of these pollutants can adversely affect soil health and crop productivity. With the rise of sustainable agriculture, there is a pressing need for effective monitoring technologies. This research project leverages hyperspectral imaging (HSI) and advanced machine learning techniques to create a scalable solution for identifying microplastics, thereby contributing to the broader field of environmental science and agricultural sustainability.
Key Details
- Application Deadline: September 30, 2025
- Shortlisted Interviews: October 2025
- Final Selection for Admission: November 2025
- Start Date: January 2026 (or earlier by agreement)
- Location: Plovdiv, Bulgaria
- Salary: €1,250/month (€15,000/year)
Eligibility & Participation
This PhD position is open to candidates with a strong interest or experience in image processing, machine learning, and environmental applications. Ideal applicants should possess skills in data analysis, coding (Python, Matlab), and scientific writing. A background in environmental science or related fields is advantageous but not mandatory.
Submission or Application Guidelines
Interested candidates should prepare the following application documents:
– Motivation letter (1–2 pages)
– Curriculum Vitae (CV)
– Academic transcripts (Bachelor’s and Master’s)
– Contact details of two academic referees
Applications should be sent directly to Dr. Hadi Mahdipour at hadi.mahdipour@au-plovdiv.bg.
Additional Context / Real-World Relevance
The integration of AI in environmental monitoring represents a significant advancement in addressing ecological challenges. By focusing on microplastic detection, this project not only contributes to academic research but also has practical implications for improving agricultural practices and ensuring food safety. The use of hyperspectral imaging combined with machine learning could set a precedent for future research in environmental applications.
Conclusion
This is an exciting opportunity for those looking to make a meaningful impact in the field of environmental science through innovative research. Interested individuals are encouraged to apply and share this opportunity with peers who may also benefit from this fully funded PhD position.
Category: PhD & Postdoc Positions
Tags: ai, machine learning, environmental science, microplastics, hyperspectral imaging, deep learning, agriculture, data science
