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Advertising division: INM-4 - Physics of Medical Imaging
Reference number: D109/2018, Computational science

PhD position: Deep Learning for multimodal data integration in functional neuroimaging

About us:
The School for Simulation and Data Sciences (SSD) at RWTH Aachen University is the consolidation of the German Research School for Simulation Sciences (GRS) and the AICES Graduate School and represents further advancements as well as new projects. The SSD closely works together with the Institute of Neuroscience and Medicine (INM) at the Research Centre Jülich. The Medical Imaging Physics (INM-4) department at INM concentrates on the development, experimental validation and the clinical implementation of novel brain imaging methods using a variety of state-of-the art neuroimaging modalities.

Background:
In this project, we aim at developing a novel data analysis workflow for multimodal data integration by means of combining different strategies from deep learning methods to optimally extract the spatial and temporal features of neurophysiological processes recorded from different neuroimaging modalities, such as, functional magnetic resonance imaging (fMRI), magneto- and electroencephalography (M/EEG). For this, we will investigate and compare various deep learning techniques to automatically extract and combine information from raw unlabeled neurophysiological data. The PhD project will offer the opportunity to also acquire expertise in neuroimaging and advanced data analysis.

Your Task:
You will develop a deep learning data analysis workflow to be applied on multimodal neuroimaging data. Validation and testing will also be performed on simulations.

Your Profile:

  • The preferable candidate holds a Master degree in computational science or related fields, preferably with experience in applications using machine learning algorithms.
  • The candidate should have strong skills in signal processing, scientific programming (preferable in Python and usage of GPUs) and substantial knowledge of Linux.
  • Ideally the candidate is experienced in processing data from neuroimaging modalities and is motivated to learn and explore various deep learning techniques.

Our offer:
We offer a position in a creative and international team with themes ranging from neuroscience and multimodal imaging, computational neuroscience and simulation technology. Research will be conducted mainly at Research Centre Jülich, but in close collaboration with RWTH Aachen University.

  • Exciting working environment on an attractive research campus at Jülich, well located in the triangle Cologne-Düsseldorf-Aachen.
  • Promotion will be at RWTH Aachen University with competent supervision by linking to the two institutes JARA-SSD (University Aachen) and INM-4 (Research Centre
    Jülich).
  • Funding will initially be provided for one year with an extension of up to additional three years upon successful completion of a scientific evaluation by the evaluation
    committee.
  • Payment of the PhD fellow will be based on salary grade EG13 (50%) Collective Agreement for the Civil Service (TVöD)

Forschungszentrum Jülich aims to employ more women in this area and therefore particularly welcomes applications from women. We also welcome applications from disabled persons.

Contact:
To apply please send a CV, a motivation letter (one page maximum) and contact details of two references until 31 August 2018 to:

Dr. Jürgen Dammers
Institute of Neuroscience and Medicine
Medical Imaging Physics (INM-4)
Forschungszentrum Jülich GMBH
52425 Jülich
Germany

Email: j.dammers@fz-juelich.de