PhD Position: Advanced Peptide Formulations and Functional Systems
Explore advanced peptide formulation at Radboud University using automation and data science. Join pioneering efforts to design functional peptide systems for biomedical and material science applications.
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Project Description
Project Overview
This project focuses on designing and analysing functional peptide systems using advanced peptide synthesis, automation, and data-driven workflows within Radboud University’s interdisciplinary Robotlab. Peptide-based systems offer versatile building blocks for therapeutic modalities and bio-based materials, but only a fraction of possible peptide sequences result in suitable functional properties. This research aims to navigate this vast complex space through automation and data analysis.
What You Will Do
You will explore peptide formulation and characterization, emphasizing structure–function relationships relevant to emerging therapeutics or bio-based surfactants. Utilizing automated analytical techniques and advanced peptide synthesis, you will examine how molecular design, formulation strategies, and environmental factors influence peptide bio-actives and materials. Collaboration with data science and machine learning experts will enable the development of data-driven frameworks guiding our understanding of peptide systems. Experimental validation will iteratively refine these models, paving the way for biomedical applications including delivery platforms and regenerative therapies.
Expected Outcomes
The project will produce novel insights into peptide formulation and functionalization, integrating automation and standardized data workflows for robust experimental interpretation. Results will drive frameworks for targeted peptide design, facilitating innovative biomedical technologies. You will disseminate findings through peer-reviewed publications, conferences, and workshops and contribute to bachelor’s and master’s education.
Why This Matters
Peptide systems hold promise for advancing therapeutic and bio-based material technologies, yet their complexity demands new approaches using automation and data science. This project’s outcomes may lead to transformative biomedical applications and sustainable materials with broad societal impact.
Entry Requirements
Eligibility
Supervisor Profile
Dr. M.F.J. Mabesoone is a researcher at Radboud University’s Faculty of Science with expertise in peptide chemistry, molecular design, and automation in chemical synthesis. His work focuses on integrating advanced synthesis methods with data-driven approaches to create novel functional peptide systems. The interdisciplinary Robotlab he is affiliated with emphasizes automated and standardized workflows, positioning him at the forefront of combining experimental peptide science with computational and machine learning methodologies.