PhD Position in Data-driven Analysis of Biological Networks
Georg-August-Universität Göttingen Department of Data-driven Analysis of Biological Networks
Germany

The Department of Data-driven Analysis of Biological Networks at the Georg-August-Universität of Göttingen invites applications for a position as

PhD student (f/m/d)

This position is available starting from November 1st, 2024. It is a part time position with a limited contract of 3 years. Salary and working hours will be according to the German grade 13 TV-L (65%, currently 25,87 hours per week).

The position will be associated with the group of Prof. Dr. Michael Wibral. We are recruiting a PhD student for the interdisciplinary research project “Evolutionary Convergence of Hierarchical Information Processing” funded by the German Research Foundation (DFG) within the research initiative SPP2205 “Evolutionary optimization of neuronal processing”. The project aims to establish the common information theoretic principles of computation in hierarchical neural systems that are conserved across species (in particular mammals and birds). Specifically, we will use the analysis of information theoretic timescales [1], the correlation of information storage and transfer [2] and the analysis of unique, redundant and synergistic information [3,4] in order to take a comparative approach to neural computation in the primate and the avian brain. The project will be pursued in close collaboration with the research groups of Viola Priesemann at the Max Planck Institute for Dynamics and Self-Organization in Göttingen and Onur Güntürkün, Jonas Rose and Roland Pusch at the Ruhr University of Bochum.

We are looking for candidates with an excellent Master degree in physics, neuroscience, cognitive science, computer science or a related field who are committed to pursuing a career in research. The successful applicant will develop novel information theoretic models and measures of neural computation and apply them to electrophysiological recordings to analyze predictive hierarchical information processing in the primate and the avian brain. The ideal candidate should possess exceptional analytical skills, coupled with a proficiency in coding in a language that is pertinent to data analysis. We offer the opportunity to become a member of a vibrant community dedicated to innovative research and teaching at the frontier of the exact and biological sciences, and to connect to the latest developments in information theory, in particular partial information decomposition.

The Göttingen Campus ( www.uni-goettingen.de/cidbn) is a leading center of biophysics and neuroscience in Europe hosting numerous internationally renowned research institutions, including the University and its Medical Center, the three Max Planck Institutes in the Life Sciences, the European Neuroscience Institute, the German Primate Center, and the Bernstein Center for Computational Neuroscience (BCCN) Göttingen.

The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The university is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled persons. In the case of equal qualifications, preference is given to applications from people with severe disabilities. A disability or equality is to be included in the application in order to protect the interests.

Please submit your application in digital form only and send all relevant documents in one single PDF-document, including a
letter of interest, your curriculum vitae with a list of publications, copies of your certificates and contact information of at
least two references to Wibral_lab@uni-goettingen.de by August,1st, 2024.
 
If you have any questions, please contact Prof. Dr. Michael Wibral
via E-Mail: michael.wibral@uni-goettingen.de

Please note:
With submission of your application, you accept the processing of your applicant data in terms of data-protection law. Further information on the legal basis and data usage is provided in the Hinweisblatt zur Datenschutzgrundverordnung (DSGVO) https://www.uni-goettingen.de/hinweisdsgvo

[1] Rudelt et al. (2021) Embedding optimization reveals long-lasting history dependence in neural spiking activity

[2] Wollstadt et al. (2023) Information-theoretic analyses of neural data to minimize the effect of researchers’ assumptions in predictive coding studies. PLOS Comp Biol 19 (11) e1011567
[3] Gutknecht et al. (2021) Bits and pieces: Understanding information decomposition from part-whole relationships and formal logic. Proc. Royal Soc. A 477 (2251), 20210110
[4] Ehrlich et al. (2023) A measure of the complexity of neural representations based on partial information decomposition, Transactions on Machine Learning Research 5  


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