Up to 4-years Ph.D. & post-doc positions are available at the Centre Hospitalier Universitaire Vaudoise (CHUV, Lausanne, Switzerland) and University of Lausanne (UNIL) funded through the Swiss National Science Foundation (SNSF), and available with an effective start date as soon as possible. Join CHUV’s Connectomics Lab to work with Prof. Patric Hagmann and his team. The Connectomics Lab is a research group at the Dept. of Radiology of CHUV involved in pioneering work on connectome mapping methods and clinical application in neurodevelopment and psychiatry. By joining the department, you’ll have access to MRI scanners for your research, as well as high-performance computing and GPU resources, while located in the very center of the vibrant Lausanne. As a Ph.D. student, your training will take place at the Lemanic Neuroscience Doctoral School (University of Lausanne) with also extensive access to courses at EPFL. Salary is in compliance with SNFS and CHUV guidelines and the contract is for up-to-four years.
You want to apply your computational and analytical skills to real neuroscientific and medical challenges? You want to propose new analytic methods to link brain structural connectivity and brain functional dynamics to behavior?
OBJECTIVES of the project. MR connectomics provides a large diversity of functional and structural brain graphs. Those multi-modal connectomes contain rich subject-specific information that is potentially related to cognition/behavior, as well as psychopathology. We propose to express connectomics data as a graph spectrum and show that specific behavioral and psychopathologic dimensions relate to specific sparse spectral representations. Hence, we expect to discover specific connectome spectral signatures (brain imaging biomarkers) of behavioral and psychopathology domains.
METHODS TO BE USED. (1) We will work with 2 MRI neuro-imaging cohorts, the open Human Connectome Project cohort (for behavior and cognition), and the Lausanne Psychosis Cohort for psychopathology. (2) In terms of projection methods, we will first, express each subject’s connectome graph signal as a spectrum using graph Fourier transform and in a second step use graph deep learning to define data-driven spectra of entire multimodal connectomes. (3) Behavior and psychopathology are expressed in terms of continuous domains using either the RDoc framework or other data-driven groupings. (4) Behavior is linked to connectome spectra is done by using various statistical methods.
✓ An MSc. / Ph.D. degree in maths/physics, electrical/biomedical engineering, signal processing/data science, or related field.
✓ The successful candidate will be a motivated researcher, open-science advocate, with self-initiative and curiosity, and a strong willingness to work in a team with other disciplines and colleagues.
✓ Experience with graph signal processing and/or machine learning will be particularly considered. ✓Proficiency in programming (Python preferred) is necessary
Please let us know your interest, and feel invited to request mentoring references for Prof. Patric Hagmann. We’ll be happy to connect you to some of his former/current students — at Connectomics Lab, your training and your career development are set first ahead of the lab’s research program.
Tagged as: Computer Science, Engineering, Life Sciences, Mathematics
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