PhD in EV-Based Secretome Therapies for Osteoarthritis

1000scholars; Utrecht; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Pension scheme

Flexible leave arrangements

Personal and professional growth

Job summary

Universiteit Utrecht invites applications for a PhD position focused on novel cell secretome-based therapeutics for osteoarthritis. The project integrates wet-lab analyses, mass spectrometry, nanoparticle analyses, and AI-driven data interpretation within a large EU-funded consortium.

In this 4-year PhD, you will explore batch-to-batch consistency, cargo-function relationships, and disease signatures in patient samples, while developing skills in both fundamental biology and translational

Qualifications

• A relevant Master’s degree in Biology, Biomedical sciences, Biopharmaceutical Sciences, Biochemistry, or related field.
• Strong background in cell biology, metabolism, immune regulation or joint biology.
• Hands-on analytical wet-lab experience and multi-omics analyses is an advantage.
• Excellent English writing and speaking skills (C1).
• Experience with data analysis using R/Python/Matlab and AI-enhanced analyses.

Responsibilities

• Conduct hands-on analytical wet-lab experiments, including cell biology analyses and multi-omics mass spectrometry.
• Perform AI-enhanced analyses and computational work on EV-enriched secretomes.
• Collaborate with EU-funded project partners across the Netherlands and abroad.
• Contribute to understanding mechanisms of EV-based therapies in osteoarthritis.

Skills

Cell biology

Mass spectrometry

Flow cytometry

Data analysis (R/Python/MATLAB)

AI-enhanced analyses

Education

Master's degree in Biology/Biomedical sciences/ Biopharmaceutical sciences

Tools

R

Python

MATLAB

Flow cytometry software

Job description

Universiteit Utrecht invites applications for a PhD position focused on novel cell secretome-based therapeutics for osteoarthritis. The project integrates wet-lab analyses, mass spectrometry, nanoparticle analyses, and AI-driven data interpretation within a large EU-funded consortium.

In this 4-year PhD, you will explore batch-to-batch consistency, cargo-function relationships, and disease signatures in patient samples, while developing skills in both fundamental biology and translational