A postdoctoral fellowship in Machine Learning for Brain Connectivity in Clinical Neuroscience
We are pleased to announce the opening of one Postdoctoral Fellowship at the Neuroinformatics Lab, an interdisciplinary initiative between the Center for Mind/Brain Sciences (CIMeC) of the University of Trento, and the Center for Digital Health of Fondazione Bruno Kessler.
The position is part of the “Neusurplan” project, an integrated approach to neurosurgery planning based on multimodal and longitudinal data. The goal is to pursue an integrated approach to pre-operative neurosurgical planning, combining structural and functional characterization of brain connectivity. The data driven strategy will take advantage of a unique dataset of intra-operative points of directed electrical stimulation and the related functional responses.
In this project, the candidate will pursue research on machine learning methods for neuroimaging data analysis to study and characterize brain connectivity, with applications to longitudinal studies and clinical practice.
The ideal candidate should have a mixed background in neuroimaging techniques and numerate disciplines, like computer science, engineering, physics, or mathematics. This project is in collaboration with the Division of Neurosurgery, S. Chiara Hospital, Trento (IT).
The position is for a 2 year Postdoc Fellowship (May, 2022 - April, 2024).
We welcome expressions of interest for this position, please contact Paolo Avesani (paolo.
avesani@unitn.it) and/or Emanuele Olivetti (
olivetti@fbk.eu) with your CV and a statement of intent.
The University of Trento ranks among top Italian Universities (
https://www.unitn.it/en/ateneo/1636/rankings).
Fondazione Bruno Kessler ranks first among the Italian research centers in Engineering and Computer Science (
https://magazine.fbk.eu/en/news/fbk-ranks-1st-in-italy-for-scientific-excellence-in-three-areas).
To also consider a work/life balance, there is more than our passion for translational research. You can check these pointers for a flavor of life quality in Trentino:
https://www.visittrentino.info/en;
https://www.discovertrento.it/enA few papers related to the project are below:
Bertò G,et al., (2021) Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation, Neuroimage, 224
https://doi.org/10.1016/j.neuroimage.2020.117402Sarubbo S, et al., (2020) Mapping critical cortical hubs and white matter pathways by direct electrical stimulation: an original functional atlas of the human brain, Neuroimage, 205
https://doi.org/10.1016/j.neuroimage.2019.116237Astolfi P, et al., (2020) Tractogram filtering of anatomically non-plausible fibers with geometric deep learning, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) LNCS, vol 12267. Springer
https://doi.org/10.1007/978-3-030-59728-3_29Sarubbo S, et al., (2021) Planning brain tumor resection using a probabilistic atlas of cortical and subcortical structures critical for functional processing: a proof of concept, Operative Neurosurgery, 20(3), 175-183
https://doi.org/10.1093/ons/opaa396