This PhD project focuses on understanding how gene-regulatory programs give rise to neuronal phenotypes and circuit function. The research integrates molecular biology, neuroscience, and artificial intelligence to connect gene regulation with neuronal activity, morphology, and connectivity. Nature Careers
Research Activities:
- Develop and apply spatial transcriptomics methods
- Measure neuronal activity and cellular morphology
- Integrate multi-modal datasets (transcriptomics, imaging, electrophysiology)
- Apply machine learning to link gene regulation with neuronal phenotypes
- Analyze and interpret gene-regulatory mechanisms
Eligibility Criteria:
- Master’s degree in molecular biology, neuroscience, bioengineering, computer science, or related field
- Background in molecular biology and/or neuroscience
- Programming skills (preferably Python)
- Interest in interdisciplinary research combining wet-lab and computational approaches
- Experience in data analysis or machine learning is preferred
Additional Skills (Preferred):
- Experience with spatial transcriptomics or genomics
- Knowledge of image analysis or single-cell data
- Familiarity with machine learning frameworks
Duration & Funding:
- Fully funded PhD position (typically 4 years)
Research Environment:
- Interdisciplinary collaboration across AI, genomics, and neuroscience
- Access to advanced sequencing, imaging, and computational infrastructure
- Opportunity to publish and present at international conferences
Start Date:
Flexible (as soon as possible)
Application Requirements:
- Motivation letter (1–1.5 pages)
- Detailed CV
- Academic transcripts and certificates
Application Process:
Apply through the official VIB online application system. VIB
