PhD position in computational analysis of neuronal RNA localization

About the role

The project aims to develop a predictive computational framework for understanding subcellular localization of polyadenylated RNAs in neurons. You will work on integrating RNA sequence, structure, RNA‑binding protein interactions and functional data to uncover localization rules in healthy, degenerating and regenerating neurons.

Key responsibilities

• Develop and evaluate machine‑learning models (including CNNs and transformers) to predict RNA localisation to neuronal cell bodies or neurites.
• Integrate diverse datasets such as Frac‑seq, N‑zip, RNA structure predictions and RBP‑binding information.
• Identify sequence and structural features driving localisation and assess changes in disease models like ALS.
• Carry out an independent research project, complete PhD coursework (≈30 ECTS), and contribute to teaching and dissemination activities.

Required profile

• Highly motivated with a strong computational background and interest in RNA biology and neuroscience.
• Excellent written and spoken English and ability to work collaboratively in an international team.
• Qualified with a Master’s degree equivalent to a Danish MSc in bioinformatics, computer science, computational biology or related field.

Required skills

• Proficiency in Python programming.
• Strong experience with Linux/Unix command‑line tools and shell scripting.
• Solid understanding of algorithms, data analysis and machine‑learning theory and implementation.
• Familiarity with basic RNA‑structure algorithms and programs.