Two Post-Doctoral Fellow positions are available in the CMI/NKI Computational Neuroimaging Lab (CNL; [computational-neuroimaging-lab.org]) under the direction of Cameron Craddock, PhD. The Computational Neuroimaging Lab is a subdivision of the Center for Biomedical Imaging and Neuromodulation (http://claymore.rfmh.org/) at the Nathan S. Kline Institute from Psychiatric Research(http://www.rfmh.org) and the Center for the Developing Brain (http://www.childmind.org/en/center-for-developing-brain/) at the Child Mind Institute (http://www.childmind.org). The lab's research agenda involves the development of novel computational analysis and experimental techniques for determining how brain function and structure are impacted by mental illness and development. Ongoing projects involve developing real-time fMRI experiments to evaluate the interaction between brain networks, applying machine learning and signal processing methods to map inter-individual variation in the human connectome, and optimizing MRI acquisition for pediatric and psychiatric populations. Additionally, the CNL is a strong supporter of open science as exemplified by developing the Configurable Pipeline for the Analysis of Connectomes (http://fcp-indi.github.io) open source software package, openly sharing data through the International Neuroimaging Datasharing Initiative(http://fcon_1000.projects.nitrc.org), and spearheading the Preprocessed Connectomes Project (http://preprocessed-connectomes-project.github.io). To facilitate their research, fellows will work as a part of a highly collaborative and multidisciplinary team that integrates a broad range of disparate specialties (e.g. cognitive neuroscience, clinical psychology, computer science, engineering, mathematics).

Post-Doctoral Fellow: development of neuroimaging data processing and analysis methods
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The primary responsibilities of this position will be to develop and evaluate analytical methods for the large scale (>> 1,000 datasets) processing and analysis of multimodal MRI neuroimaging data. Using multivariate methods, the incumbent will integrate information from disparate imaging modalities to identify clinically relevant subpopulations and related neurophenotypes from datasets that span a variety of disorders. The incumbent will be expected to conduct large-scale neuroimaging analyses (functional, structural, and diffusion MRI). They will mentor and in some cases supervise junior lab members such as research associates and graduate students. They must be able to work effectively in a very collaborative and multidisciplinary environment, write scientific manuscripts, and orally present their work.

Qualifications:
- PhD in biomedical engineering, cognitive science, electrical engineering, mathematics, or physics.
- Significant prior neuroimaging experience with MRI, with strong skills in preprocessing and analyzing neuroimaging data using one or more of the common neuroimaging packages (e.g., AFNI, FSL, Freesurfer, Diffusion Toolkit, or SPM).
- Programming experience in C/C++, Matlab, Python, and similar platforms.

Post-Doctoral Fellow: Probing brain networks with real-time fMRI
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The primary responsibility of this research position will be to investigate the role of network dysregulation in psychiatric disorders using real-time fMRI. This will involve developing and maintaining a real-time fMRI system, as well as designing, implementing and performing real-time fMRI experiments. The incumbent will be expected to conduct large-scale neuroimaging analyses (functional, structural, and diffusion MRI). They will mentor and in some cases supervise junior lab members such as research associates and graduate students. They must be able to work effectively in a very collaborative and multidisciplinary environment, write scientific manuscripts, and orally present their work.

Qualifications:
- PhD in biomedical engineering, cognitive science, electrical engineering, mathematics, or physics.
- Research experience with functional, structural, and diffusion MRI acquisition and analysis.
- Proficient with common neuroimaging tools (AFNI, FSL, SPM, Freesurfer, etc.), as well as programming C/C++, Python, and shell scripting.
- Strong skills in using data analysis tools such as Matlab and R.
- Prior real-time fMRI and/or MRI sequence development experience is a strong plus.

Salary and Anticipated Start Date: Salary is competitive and commensurate with experience/educational qualifications. Benefits include health, vision, and dental. Anticipated Start Date is immediate.

Application details: Please email cameron.craddock@childmind.org to apply, please include a CV including the names of 3 references with your inquiry.

Employment at Will Relationship: This position description does not constitute a guarantee that employment will continue for any specified period of time. Rather, employment is at the mutual consent of the employee and CMI, and can be terminated at will by the employee or by CMI.

CMI reserves the right to modify the job description and/or reporting relationship at any time.

CMI is an Equal Opportunity Employer. CMI is committed to recruiting and maintaining a diverse staff; individuals from all backgrounds are strongly encouraged to apply.

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Cameron Craddock, PhD

Director of Imaging, Center for the Developing Brain
Child Mind Institute
childmind.org
445 Park Avenue (entrance on 56th Street)
New York, NY 10022

Director, Computational Neuroimaging Laboratory
Nathan S. Kline Institute for Psychiatric Research
www.rfmh.org/nki
1040 Old Orangeburg Road
Orangeburg, NY, 10962