PhD Position - Multi-Scale Data-Driven Model of Synaptic Function and Resilience

Your Job :

Healthy brain function relies on dynamic changes at the synapse. The relevant synaptic turnover and plasticity processes span spatial scales from the molecular up to the network level, and temporal scales from seconds to hours and beyond.

The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between synaptic resilience and the reliability of synaptic responses. The work primarily involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation.

Your Profile :

A Masters degree with a strong academic background in physics, mathematics, computer science, computational neuroscience, or a related field

Excellent quantitative and analytical skills

Proficiency in at least one programming language (Python, C++, …)

Keen interest in neuroscience is essential

Experience with modelling, analysis of complex dynamical systems, simulation, analysis of large-scale datasets with machine learning methods, and software development are beneficial

Good organisational skills and ability to work systematically, independently and collaboratively

Effective communication skills and an interest in contributing to a highly international and interdisciplinary team

Working proficiency in English for daily communication and professional contexts (TOEFL or equivalent or excemption required)

• Knowledge of German is beneficial

Our Offer :

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with :

ENVIRONMENT : World class science environment at the interface between neuroscience and digital technologies, enabling scientific progress on the most complex known systems