PhD Position - AI-Based Microplastic Detection in Recycled Organic Fertilisers

The Centre for Cleantech and Biomass Resource Efficiency is seeking an exceptional and highly motivated PhD student to contribute to pioneering work in the development of sustainable phosphorus-enriched organic fertilisers. This research aims to address the critical global challenge of phosphorus scarcity by innovating a locally sourced, environmentally sustainable alternative to conventional synthetic fertilisers. This fully funded position offers a unique opportunity to engage in cutting-edge research with significant implications for sustainable agriculture and resource recycling.

 Project Overview

The project addresses a pressing agricultural and environmental issue: the presence of microplastics (MPs < 5 mm) in recycled fertilisers derived from composting and anaerobic digestion. Concerns over soil contamination have led to a hesitation in adopting these sustainable fertilisers across Europe, particularly in Bulgaria.

Traditional MP detection methods (chemical extraction + FTIR/Raman spectroscopy) are time-consuming and inefficient. This project aims to develop a faster, AI-powered method using Hyperspectral Imaging (HSI) to enable reliable, scalable microplastic quantification in real-world agricultural samples.

Research Focus

This research focuses on building a novel HSI-AI pipeline for the detection and quantification of microplastics in organic fertilisers. Key activities include:

• Developing a robust and fast HSI-based detection method using deep learning (CNNs and pixel-wise classification).
• Creating a comprehensive dataset of hyperspectral images for training and testing models.
• Implementing and evaluating preprocessing steps to improve model performance and computational efficiency.
• Comparing model performance and cost-efficiency with traditional detection methods.
• Testing the technology in lab and field settings using real-world composting and digestion samples.

Job Description

This is an interdisciplinary position requiring interest and/or experience in the following areas:

• Image processing and sensor data analysis, ideally with HSI or other imaging technologies.
• Machine learning and artificial intelligence, especially classification and segmentation tasks.
• High-dimensional and big data analysis related to spectral imaging.
• Data management and dataset creation for AI training.
• Programming skills in Python, Matlab, or similar platforms.
• Scientific writing and reporting; publication and presentation experience.
• Background or interest in environmental science or sustainable agriculture is a plus.

Candidate Requirements

• A completed Master’s degree in a relevant field (e.g., Computer Science, Environmental Engineering, Electrical Engineering, Physics, Applied Mathematics, or a related area).
• Strong interest in applying AI to environmental challenges.
• Good communication skills and fluency in English.

Why Choose Plovdiv?

Plovdiv, Bulgaria’s cultural capital and one of Europe’s oldest cities, offers an unparalleled environment for your PhD journey. This vibrant city combines a rich historical legacy with a thriving modern lifestyle. Enjoy a dynamic arts scene, scenic Rhodope Mountains, and a warm international community. With a low cost of living and a high quality of life, Plovdiv is not just a place to study—it’s a place to live, grow, and be inspired.

Position Details

• Starting Date: January 2026 or earlier by agreement.
• Location: Agricultural University of Plovdiv, Bulgaria
• Salary: €1,250/month (€15,000/year), offering high purchasing power by Bulgarian standards.
• Contract Type: Full-time PhD (3–4 years).

Application Instructions

Interested candidates should prepare the following documents:

• Motivation letter (1–2 pages)
• CV (highlighting relevant skills, experience, and publications)
• Transcripts from undergraduate and master’s studies
• Contact information for two academic referees 

Please send your application by email to: cmd_au@abv.bg

Contact person: Kostadinka Popova

Tel.:032/654231