3 X Master’s Thesis Projects/internships in Human Ultrahigh Resolution Neuroimaging of High-level Cognition

Tübingen                 ·                Part time

3 x Master’s thesis projects/internships in human ultrahigh resolution neuroimaging of high-level cognition

Job Offer from February 22, 2024

The newly established Cognitive Neuroscience & Neurotechnology group led by Dr. Romy Lorenz is looking for enthusiastic Master’s students to work on the exciting field of ultrahigh resolution fMRI that allows to investigate the human cortex at the scale of layers and columns.

Our lab focuses on advancing our understanding of the frontoparietal brain network mechanisms that underpin high-level cognition and adaptive behaviour. For this, we pursue an interdisciplinary research programme that allows studying this brain system at multiple levels of granularity. Our methodology involves subject-specific brain-computer interface technology, fMRI at 3T and ultrahigh (i.e., 7T and 9.4T) magnetic field strengths (for resolving cortical layers), EEG, non-invasive brain stimulation as well as machine learning. You can find out more about our work at: https://www.kyb.tuebingen.mpg.de/711763/cognitive-neuroscience-neurotechnology

You can choose among the three following research projects:

1. Individual-level network mapping: You will investigate the precise extent and topography of the frontoparietal network within individual healthy volunteers and understand how the topography of the frontoparietal network is affected by layer-specific connectivity. This data analytics project will leverage an existing resting-state dataset using ultrahigh resolution GE-BOLD fMRI at 7T with a submillimetre voxel resolution to resolve cortical layers.
2. Dynamic layer-specific connectivity in working memory: You will investigate the adaptation of information flow between cortical layers within the frontoparietal network in response to varying task demands. This data analytics project will leverage an existing task dataset acquired using ultrahigh resolution VASO fMRI at 7T with a submillimetre voxel resolution to resolve cortical layers. While VASO fMRI has a lower temporal resolution than GE-BOLD, you will benefit from it’s higher layer-specificity.
3. Optimize anatomical processing pipeline: First, you will conduct benchmarking of our in- house pipeline (in Bash/Python), originally developed for ultrahigh resolution data at 7T, to assess its performance with 9.4T data. Next, you will optimize processing steps (e.g., brain masking, bias correction, segmentation, registration, layer definition) and tailor them to 9.4T data. This may also involve acquiring novel structural data that could further improve our results.

Applicants should demonstrate a keen interest in high-level cognition research and are Master’s students in cognitive (neuro)science, psychology, computer science, mathematics or related disciplines. Good programming skills in Bash and Python are required. Prior experience with (f)MRI data is highly desirable but not necessary. Equally, experience with high-performance computing clusters and code sharing platforms (e.g. GitHub) are desirable.

The Max Planck Society seeks to employ more people with disabilities and strongly encourages them to apply. Furthermore, we actively support the compatibility of work and family life. The Max Planck Society strives for gender equality and diversity.

The positions are available from April 2024 on (duration: 6-9 months) and will remain open until filled. Please send your application containing a motivation letter (specifying the project you are applying to), CV, certificates/transcript of records, names and contact details of 2-3 referees, and desired starting date as a single PDF file to Dr. Romy Lorenz (romy.lorenz@tuebingen.mpg.de).

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