Connectionists: Postdoc in Machine learning applied to brain activity data

[Erik Fransén]

Postdoc in Machine learning applied to brain activity data

We are seeking a candidate with a PhD in one of the following areas Machine Learning, Computational Neuroscience, Computer Science or Physics.

The project will entail analysis of neural data. We are currently analyzing data from Parkinson’s patients (eye-tracking, MEG) and extracting features to be used for disease diagnostics and prediction. The candidate will work in close collaboration with other postdocs and PIs in the consortium.

dBRAIN is an interdisciplinary initiative to better understand neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease. We combine brain imaging, machine learning, topological data analysis and computational modelling of biological neural networks at multiple scales to identify causal links among disease biomarkers and disease symptoms. This understanding should improve diagnosis, prediction of the disease progression and suggest better therapies.

For more information about the position and to apply, visit the web site:
https://www.kth.se/en/api/2.61673/what:job/jobID:432976/where:4/
Deadline for application: 01.Nov.2021 11:59 PM CET


Prof. Erik Fransén
Dept. of Computational Science and Technology
School of Electrical Engineering and Computer Science
KTH Royal Institute of Technology
Stockholm, Sweden
https://www.kth.se/profile/erikf
https://scholar.google.se/citations?user=VFtGuvcAAAAJ&hl=sv


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