The PhD project will address how learning induces connectome changes that implement the formation of a synaptic memory trace in cortical networks and how such a distributed memory trace becomes robust against alterations of individual synaptic connections in the presence of constant synaptic turnover. In particular, we will develop computational models of the dynamics of the excitatory and inhibitory connectome in the mouse cortex during learning to explain learning dynamics in terms of fundamental underlying plasticity mechanisms and characterize the conditions for the formation of lasting memories. The research will be performed in close collaboration with the labs of Simon Rumpel (University of Mainz, experimental collaborator) and Matthias Kaschube (FIAS, Frankfurt, theoretical collaborator) and Jürgen Jost (MPI for Mathematics in the Sciences, Leipzig, theoretical collaborator). The project is embedded in Germany’s priority program “Computational Connectomics” (https://spp2041.de).

For further information on the Triesch Group and FIAS please see (https://www.fias.science/en/life-and-neurosciences/research-groups/jochen-triesch/)

We are looking for candidates with:
• An excellent master’s degree in Computational Neuroscience or a related field (Physics, Computer Science, Mathematics, Engineering, etc.)
• Excellent communication skills and working proficiency in English
• A strong interest in interdisciplinary research
• Previous experience in spiking neural network simulations
• A broad knowledge of Computational Neuroscience and neural plasticity
• A strong interest in collaborating with experimental labs is a plus.

We offer:
• A highly inspiring work atmosphere
• Exciting and modern research topics bridging theory and experiment.
• An excellent research infrastructure and dedicated mentoring.
• Excellent opportunities for training and career development. You will be affiliated to the Goethe-University and a fellow of the graduate schools GRADE-iQbio and FIGSS.
• PhD candidates will profit from synergies emerging through the interaction with their experimental / theoretical co-fellow.
• You will have the opportunity to live in Frankfurt am Main, a vibrant and exciting cosmopolitan city at the heart of Europe.
• A funded PhD position with competitive salary (65%, based on TV-H E13)

Required documents:
• A motivation letter, stressing why you want to do a PhD in the field and in our lab.
• A detailed curriculum vitae containing academic qualifications, research experiences, skills, possibly a publication list where you highlight your contribution.
• Name and contact information of at least two scientists who can give references.
• Detailed transcripts of records of your Master’s and Bachelor’s programs.


Please upload all documents as a single pdf file to Prof. Dr. Jochen Triesch: https://pm.fias.science/projects/application

Applications may be submitted until September 30, 2022 but interviews will be scheduled as soon as possible. The successful applicant is expected to start in late 2022 / early 2023.


Frankfurt Institute for Advanced Studies (FIAS)
Ruth-Moufang-Str. 1, 60438 Frankfurt am Main
https://fias.uni-frankfurt.de

The Frankfurt Institute for Advanced Studies (FIAS) is an international research institute for interdisciplinary theoretical Research in the Rhine-Main-Area. It is an institute with activities in Natural Sciences, Life Sciences & Neurosciences and Computer Sciences, dedicated to cross-disciplinary research and to promotion of young scientists. The hierarchy at FIAS is flat and all fellows have same rights and obligations. Our institute is dedicated to building a diverse community in its training and employment programs.
FIAS is positioned at the Science-Campus Riedberg hosting, in addition, the institutes of life science and science departments of the Goethe University Frankfurt, the Max-Planck Institutes for Biophysics und Brain Research and the Frankfurter Innovation center FIZ. Frankfurt creates a superb environment for researchers at FIAS with its global internet hub, the active software enterprises, and its strategic importance in fields of finance, medicine, mobility and pharmaceutic industry (and their large data sets) eager to cooperate with fundamental sciences.