Permanent scientist position opened in CEA (Atomic Energy Commission), Life Sciences Division, NeuroSpin neuroimaging center (http://www-dsv.cea.fr/en/institutes/institute-of-biomedical-imaging-i2bm/departments/neurospin-neurospin) within the BrainOmics team.

The BrainOmics Team (3 senior scientists, 2 postdocs and 1 or 2 PhD studients) is in charge of the research and development in imaging-genetics (see en.wikipedia.org/wiki/Imaging_genetics) which is a field at the intersection of neuroinformatics, bioinformatics, applied statistics, and machine learning [1, 2]. The team is involved in several French and European projects (ANR IA Brainomics, FP6-FP7 IMAGEN and IMI EU-AIMS).

The team has collaborations with other groups in NeuroSpin for structural image processing (team LNAO) or machine learning/fMRI (team INRIA-CEA/Parietal). NeuroSpin is an international research institute in which very high field MRIs are designed and operated to carry out studies in neurosciences, and clinical/pre-clinical research. NeuroSpin co-leads the CATI platform (neuroimaging for the French Plan Alzheimer) and is a part of the new Paris-Saclay Campus.

The researcher will explore the role of genetics and environmental disturbances in the variability of rich phenotypes originating from imaging and/or medical, behavioral scores. Applications are expected for new biomarker discovery and basic research in neurosciences (e.g. development, ageing). The research will be (not exclusively) performed on the neuroimaging-genetics cohorts being built at NeuroSpin (IMAGEN, EU-AIMS, Senior, ...) for studies in neuroscience, neurodegenerative diseases, psychiatric syndromes, and possibly in oncology or preclinical studies.

Conditions:

•  Starting time: Summer, Fall 2015
•  Salary will be commensurate with experience

To apply:

To submit your application, please click on the "APPLY" button. The application (in French or English) should include a cover letter specifying your motivation and research experience as well as a CV. Please feel free to contact us if you have any questions.

• Ph.D. in applied mathematics, computer science, bioinformatics, image processing, biostatistics, machine learning, genetic epidemiology or related disciplines.The initial training may include biology, medical imaging.
•  Experience in applying and developing machine learning techniques in massive high-dimensional data (n~10^3, p~10^6). Any experience related to the use/development of univariate/multivariate methods for association/heritability studies between imaging phenotypes and genetic measures, epigenetic and gene expression.
• Strong experience in scientific programming C/C++, ideally in Python language.
• Good communication skills to work in a multi-professional team. The candidate spent one or more PostDoc periods in scientific fields related with imaging-genetics. She/He published several papers as a first author, and built a working relationship network in related scientific fields. She/He potentially already wrote funding requests and managed scientific projects.
• Interest and knowledge in neuroimaging, neuroinformatics and bioinformatics will be appreciated. 

References

[1] Whelan, R., Watts, R., Orr, et al. « Neuropsychosocial profiles of current and future adolescent alcohol misusers. » Nature, 512(7513), 185–9. 2014.

[2] E. Le Floch, V. Guillemot, V. Frouin, P. Pinel, C. Lalanne, L. Trinchera, A. Tenenhaus, A. Moreno, M. Zilbovicius, T. Bourgeron, S. Dehaene, B. Thirion, J.-B. Poline, and E. Duchesnay, « Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares. » NeuroImage, vol. 63, no. 1, pp. 11–24, 2012.