Skip to main content

This job has expired

Postdoctoral Position in Evolutionary Diffusion MRI Brain Connectivity

Employer
Max Planck Institute for Human Cognitive and Brain Sciences
Location
Germany (DE)
Salary
pay scale of the Max Planck Society (TVöD Bund E 13)
Closing date
Jul 22, 2022

View more

Discipline
Life Sciences, Evolutionary Biology, Neuroscience
Position Type
Full Time
Job Type
Postdoc
Organization Type
Non-Profit

 

 

The Department of Neuropsychology (Director: A. D. Friederici) at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS, Leipzig, Germany) has an opening for a

Postdoctoral Position in Evolutionary Diffusion MRI Brain Connectivity

The position is initially offered for two years in the collaborative project “Evolution of Brain Connectivity” between the MPI CBS, the MPI for Evolutionary Anthropology, and the Institute for Cognitive Sciences of the CNRS in Lyon, France. The research project focuses on the evolutionary trajectory of brain connectivity between nonhuman primates and humans. MRI data of the brain is collected in an ethical and sustainable manner from nonhuman primates that died naturally in the wild, in sanctuaries, and zoos. The newly established post-mortem diffusion MRI (dMRI) protocol provides data of unpreceded resolution and quality and allows us to address new questions related to evolution.

 

The successful candidate will work in an international and multidisciplinary team, focusing on the comparative analysis of language-related fiber pathways. By combining existing behavioral and brain connectivity data of wild chimpanzees and other primates, the position allows a unique possibility to study the function-structure association from an individual and phylogenetic perspective. In addition, the wide range of collected primate species will allow the creation of sophisticated models of brain evolution and of the function of neural fiber connections in the brain.

 

In close collaboration, the position also includes dMRI data acquisition of newly collected brain samples. The ideal candidate should have a sound methodological background in image processing, dMRI analysis, and tractography with available tools (e.g., FSL, MRtrix), as well as good programming skills (e.g., Bash, MATLAB, Python, R), and experience in statistical modeling using behavioral data. The candidate must hold a PhD in computer science, engineering, cognitive neuroscience, or a related field, demonstrate an academic record including international publications, and be highly proficient in spoken and written English. Previous experience and a strong interest in evolutionary brain research and modeling are desired.

 

The position is available immediately. The duration of the post is two years. Remuneration is based on the pay scale of the Max Planck Society (TVöD Bund E 13). Social benefits correspond to those of the civil service.

The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Furthermore, the Max Planck Society strives for gender equity and welcomes applications from all backgrounds.

 

Please submit your application via our online system (subject heading “PD 16/22”). The position will be filled as soon as a suitable candidate is found.

Leipzig is a vibrant city that has been called “Germany’s new cultural hot spot” by the Guardian and listed as one of the 52 places to go in 2020 by the New York Times. It has a long-standing history of classical music, academic education, and more recently modern arts. With its many parks, forests, canals, and lakes, Leipzig is a perfect place for recreation, sports, and leisure time. It is located an one-hour train ride south of Berlin.

Applicants are encouraged to contact Dr. A. Anwander (anwander@cbs.mpg.de) for more details concerning the position. Further information: http://www.cbs.mpg.de

 

Get job alerts

Create a job alert and receive personalized job recommendations straight to your inbox.

Create alert