Please find the following job posting:

_______________________________________________________________________________ Job offer: https://team.inria.fr/parietal/job-offers/

Motivational blog post: http://gael-varoquaux.info/blog/?p=175 _______________________________________________________________________________

We are looking for a research engineer to assist us in applying leading-edge machine-learning methodology to large databases of fMRI resting-state functional-connectivity.

In a few words, we want to leverage the nilearn (http://nilearn.github.io) library for machine learning on brain imaging as well as internal research in the Parietal team (http://http://team.inria.fr/parietal/) at INRIA, to learn predictive biomarkers of pathologies from unique large fMRI databases. These databases are hosted at the CATI (http://cati-neuroimaging.com/) and encompas multiple pathologies, with match control subjects, aquired nation-wide in France.

As a research engineer, you will be taking part to the NiConnect research project (http://parietal.saclay.inria.fr/research/spatial_patterns/niconnect), developing tools for the analysis of "functional connectomes": brain connectivity infered using functional MRI. The project unites neuroscientists, data-miners, statisticians and clinical researchers to transfer recent advances in basic neuroscience to clinical diagnostic tools. You will work hand in hand with the computer science and statistics researchers, as well as the clinical researchers.

Your duties will be:

* to integrate the functional-connectivity tools developed in nilearn * into the CATI analysis pipelines. * to validate functional-connectivity approaches and extract new * bio-markers for specific applications to dementias using CATI datasets. Targeted applications include the prediction of Alzheimer's disease based on the unique nation-wise cohort of elderly people that is managed by CATI. * to assist writing publications in relation with those activities. * to contribute to the nilearn library (http://nilearn.github.io) in order to make functional-connectivity analysis on large cohorts easier.

You will be employed by CATI (http://cati-neuroimaging.com/) (itself part of CEA, which manages the Neurospin brain-imaging platform), but you will be embedded in the Parietal computer science group (http://http://team.inria.fr/parietal/) in which I group, and that is affiliated to INRIA, the French computer science research institute.

Requirements =============

* Masters or PhD in computer science, electrical engineering, * neuro-imaging or a related field. * Previous experience with medical imaging/neuroimaging * Good technical English level * A goal-oriented, practical approach to running data analysis * Knowledge in image processing, statistical analysis or machine learning desired * Programming experience, in particular in Python and/or open source libraries, welcomed * Some knowledge of Linux/Unix appreciated * Experience with a computing cluster is a plus

Speaking French is not a requirement, as it is an international team.

Why apply to this job? ======================

As for any job, the best reason to apply to this job would be because you are excited to learn new things. Parietal and CATI are highly-skilled environment, with expertize in advanced neuroimaging data processing, machine learning, statistics, neuroscience, and high-quality software development in Python.

About the team ===================

Working at Parietal is a unique opportunity to be at the core of statistical methodological research for neuroimaging and to improve your skills in data processing in Python.

Parietal (https://team.inria.fr/parietal/) is part of INRIA (http://www.inria.fr), the French computer science research institute, recognized world-wide as one of the leading computer-science research institutions. Parietal is a small research team (around 20 people) with a fine understanding of statistical and algorithmic issues in neuroimaging data processing as well as an excellent technical knowledge of scientific computing in Python.

Parietal is committed to helping to build an open-source neuroimaging data-processing community. its members are core developers in central projects Python data-processing tools such as the nilearn (http://nilearn.github.io) library for machine learning applied to NeuroImaging, scikit-learn (http://scikit-learn.org), the reference machine learning library in Python, Mayavi (http://docs.enthought.com/mayavi/mayavi/) for 3D visualization, as well as the nipy (http://nipy.org) library for NeuroImaging.

(CATI<http://cati-neuroimaging.com/) is the national core facility for multicenter neuroimaging studies. CATI brings together neuroimaging research laboratories with complementary expertise located at NeuroSpin, the largest French MR research institute, and in La Pitié-Salpêtrière Hospital, the largest French hospital. CATI's services cover standardization of MRI data acquisitions, data transfer to a centralized database, monitoring and quality control, and image analysis using a large portfolio of tools that include machine learning approaches. Initially designed to address Alzheimer's disease- specific needs, the platform is now open to academic research projects and therapeutic trials targeting any neuropsychiatric disorder. CATI's core laboratories have many years of experience in the coordination of multi-site neuroimaging research. Its infrastructure stretches across the country, collecting additional know-how from all the French groups and organizations involved in neuroimaging, in order to offer the best tools for scientific projects. CATI has already received over 5000 exams from its harmonized network of over 50 sites. Over 10000 images of multiple modalities (anatomical MRI, functional MRI, diffusion MRI, PET, SPECT) have been processed resulting in various anatomical and functional measures. CATI is a core member of the NiConnect project.

Parietal as well as the core team of CATI are located in the Neurospin brain research facility (http://www-dsv.cea.fr/en/instituts/institut-d-imagerie-biomedicale-i2bm/serv...), that hosts several brain scanners and research teams in neuroscience and medical imaging.

Contact Info ==============

* Technical Contact: Gael Varoquaux * E-mail contact: gael.varoquaux@inria.fr * HR Contact: Catherine Champseix * E-mail Contact: catherine.champseix@gmail.com * No telecommuting * Fixed-term contract. Duration 24 month, with possible extension of 12 * months. * Salary depending on experience * Experience required: some professional experience in neuroimaging or data processing