Using mathematical and computational approaches, we study how neurons and the synaptic connections between them tune their properties during early development and young life to ensure appropriate network dynamics and behavior. Another interest relates to how adult function and behavior emerge from a diversity of mechanisms, including synaptic plasticity, sensory noise, and biophysical constraints. We address these questions at different spatial scales, from the organization of individual synaptic inputs on dendrites to large-scale networks of higher order cortex. We are especially interested in these processes during development before and shortly after birth when the brain is highly plastic, but general aspects of learning and memory, especially under naturalistic stimuli and behaviors are also of interest.

We collaborate with different experimental research groups in the US, UK, Netherlands, Spain and Germany and benefit from interactions with the strong neuroscience community in Munich, including the SyNergy Cluster of Excellence. Our applications range across animals from rodent to Drosophila to reptiles and humans.

Successful applicants can choose from a range of projects including theoretical model development and analytical calculations, numerical simulations, and applications to rich datasets from collaborating labs. Open topics include:

- Formation and co-organization of excitatory and inhibitory synaptic inputs on dendrites, including dendritic growth, receptive field formation and alignment, and emergence of tuning.

- Development of biophysical models of synaptic plasticity at the cellular and subcellular levels and investigation of their functional consequences.

- Reliable top-down modulation of network dynamics during synaptic plasticity, including interactions between different information streams.

- Mechanistic dissection of cortical computations driven by different cell types, especially interneurons. 

- Modeling network attractor states of resilience, and synaptic and homeostatic plasticity processes to rebalance network states after perturbation.

Please check our website for recent publications: https://www1.ls.tum.de/compneuro/publications/

Applicants should have a strong quantitative background (in mathematics, physics, engineering, computer science, or related fields) and excellent programming skills (Julia, Python, Matlab or C/C++).

The positions can start at any time. For more information or an informal discussion, email me at gjorgjieva@tum.de.

To apply for these positions, please email the following:

1. A curriculum vitae

2. A description of research interests, including a motivation for why you chose to apply to our group
3. A writing sample, either a paper or code
4. Contact details for 2-3 referees
5. Transcripts (if applying for a PhD position)