미국 LA에 있는 USC 의과대학 뇌영상정보학과에서 post-doc을 모집합니다. Brain structural MRI (T1w MRI) image processing 또는 analysis, DTI or rs-fMRI쪽 분석에 연구를 하고 있거나, 비슷한 분야에서 연구를 하고 계신 박사학위 예정자 또는 post-doc연구원을 모집합니다. 관심이 있으신 분은 CV를 작성해서 hosung.kim@loni.usc.edu에 보내주시기 바랍니다. 자세한 사항은 아래 내용을 참고해 주시기 바랍니다.
Postdoctoral Fellow Position in Multicontrast MRI Analysis for Neurodevelopment and Big Data
Keck School of Medicine of USC
University of Southern California
Laboratory of Neuro Imaging (LONI), Neuroimaging and Informatics Institute
Duration: 2 years (option to renew for additional years)
Start date: Soon as possible or Spring (start date is negotiable)
Salary: Depends on experience, in accordance with NIH guidelines
Overview:
The focus of research is on developing image processing and image analysis techniques for multivariate analysis of various imaging-features that are extracted on human brain MRI. One main project that the selected postdoc fellow may participate in is to advance part of the present pipeline for morphometry of neonatal and infant brain MRI and/or for DTI / rs-fMRI analyses in order to automatically perform multicontrast image analyses. Other main project may include development of techniques for prediction of surgical / neurodevelopmental outcome using machine-learning algorithms applied to BIG DATA combining imaging-features with psychological / behavioral parameters, clinical parameters and genetic data. The laboratory provides ample opportunity for the development of innovative, focused research and a broad collaborative clinical neuroscience experience as well as for numerous publications in high impact journals.
Required Qualifications:
Position qualifications include a Ph.D. in neuroscience, biomedical engineering, computer science or a related field. The successful applicant will have expertise in anatomical MRI, diffusion tensor imaging (DTI) or resting-state fMRI analysis, strong skills in imaging processing such as registration, segmentation and/or surface modeling, statistical methods such as statistical parametric modeling, voxel-based / deformation-based morphometry or graph theory for the structural / functional connectivity analysis. Experience with neuroimaging analysis programs (AFNI, FSL, SPM, FreeSurfer or other relevant programs), and statistical analysis (MATLAB & toolbox – SPM, SurfStat, R) are also required. A person with expertise in machine learning approaches such as deep learning (DNN, CNN) / various classification methods (SVM, probabilistic graphical models, ensemble models) would be highly encouraged. Excellent scientific writing skills and strong publication records are highly desired. Solid big data programming skills with a working knowledge of Linux, C/C++, Python (scikit-learn, Theano, PyMVPA), and Matlab is desirable. Applicants should be able to work independently and with a small amount of supervision, but should also demonstrate interpersonal skills and an interesting in working collaboratively. Salary and benefits are competitive.
Candidates should submit cover letter, CV and concise description of research interests & career goals to Dr. Hosung Kim (hosung.kim@loni.usc.edu).
For further information, applicants should contact:
Hosung Kim, Ph.D.
Assistant Professor, Laboratory of Neuro Imaging (LONI) Email: hosung.kim@loni.usc.edu