Fluorescence Data Analysis for Microplastic Detection (ref. BAP-2025-7)

The Roeffaers Lab at KU Leuven develops cutting-edge microscopy techniques to address key challenges in environmental science, catalysis, and biomedical research. Our team specializes in fluorescence and Raman-based approaches, integrating advanced microscopic analysis to gain molecular-level insights into complex materials and systems. The lab is internationally recognized for its expertise in correlative imaging and materials science.

To advance our microplastics research, we seek a highly motivated Postdoctoral Researcher with expertise in (fluorescence) microscopy data analysis, chemometrics, and machine learning. The project focuses on developing scalable, accreditation-ready workflows for detecting microplastics in challenging matrices such as water, beverages, and biological samples.

As a key team member, you will:
- Develop advanced imaging pipelines to classify microplastics based on fluorescence signatures while minimizing false positives.
- Automate high-throughput workflows and optimize polymer-specific detection using chemometrics and machine learning.
- Validate detection methods using diverse samples to align with international regulatory standards.

You will collaborate with a multidisciplinary team of materials scientists, engineers, and external partners, contributing to fundamental research and technology valorization. This role provides access to state-of-the-art facilities, including fluorescence and Raman microscopes, supporting your professional development and enabling high-impact research.

If you are passionate about data-driven environmental innovation and eager to transform research into real-world solutions, we invite you to apply.

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Responsibilities

- Optimize fluorescence-based microplastic identification protocols utilizing existing data, incorporating hyperspectral imaging and fluorescence lifetime analysis for comprehensive characterization.- Develop advanced data analysis pipelines, including chemometric and machine learning models, to classify different types of polymers and non-polymers.- Automate high-throughput imaging workflows to handle large sample volumes, integrating hardware and software solutions for rapid, reliable MP detection.- Validate the detection methods using diverse sample types and ensure compliance with emerging regulatory standards.- Collaborate closely with a multidisciplinary team, including materials scientists, environmental engineers, and industry partners, to translate fundamental research into market-ready solutions.- Disseminate research findings through scientific publications, conference presentations, and stakeholder meetings, and contribute to patent applications and valorization strategies.

Profile

A PhD in data science, chemistry, materials science, physics, bioengineering, or a related field.Proven expertise in fluorescence microscopy, image processing, and data analysis methods.Experience with chemometrics, machine learning, or deep learning techniques for pattern recognition and classification tasks.Familiarity with fluorescence microscopy, environmental analysis, or microplastic research is a plus.Strong analytical, organizational, and communication skills, with a demonstrated ability to work both independently and as part of a team.A publication track record in relevant fields and a proactive attitude towards technology valorization and service development.

Offer

A dynamic research environment with state-of-the-art facilities and close collaborations with industry and governmental stakeholders.An opportunity to contribute to high-impact environmental and public health innovations, shaping the future of microplastics detection methodologies.Support for professional development, networking, and career advancement.

Interested?

For more information please contact Prof. dr. ir. Maarten Roeffaers, tel.: +32 16 32 74 49, mail: maarten.roeffaers@kuleuven.be.You can apply for this job no later than February 16, 2025 via the online application tool

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