领域：Machine Learning, biomedical,bioinformatics

方向：image analysis; analyzingmassive genomic data; molecular and cellular biology

Postdoctoralposition:

1 machine learning are Bayesian inference, convexprogramming, large-margin classifiers, kernel machines and in biomedicalimage analysis are 3Dsegmentation and morphological characterization

2 develop advanced sparse machine learningand bioinformatics strategies for multidimensional brain imaging genetics

3 developing machine learning algorithms toaddress the computational challenges of analyzing massive genomic data for variousbiological applications

Postdoctoralposition in bioinformatics and machine learning：

EMPLOYER: Institute for Genomics andMultiscale Biology, Mount Sinai School of Medicine

LOCATION: New YorkUnited States

The group focuses on developing andapplying machine learning methods to build network and predictive models of biological processes from large genomic data sets.Some of the specific areas my group is currently focusing on are the modeling of the immune response system, prediction ofbreast cancer phenotypes, and the discovery of novel therapeutics,especially synergistic drug pairs.

Ideal applicants should have a backgroundon biomedical image analysis, computer vision, patternrecognition and/or machine learning.

Postdoctoralposition：

New York State Center of Excellence inBioinformatics and Life Sciences, The State University of New York at Buffalo：

The major research focus is on developingmachine learning algorithms to address the computational challenges of analyzing massive genomic data for various biologicalapplications.

Postdoctoralposition in Biomedical Informatics：

for candidates with strong skills in atleast one of the following areas: applied math, machinelearning, data mining, signal processing, mathematical modeling, biostatistics,neural engineering.  

Candidates with particular interest in applyingtheir analytic and informatics skills toward building biomedicaland healthcare applications will surely enjoy the range of projects thatwe are pursing.

BerkeleyLab Recruiters, Lawrence Berkeley National Laboratory：

Our laboratory offers training and researchopportunities in digital tomosynthesis, image analysis and computer-aid diagnosis,including development of new reconstruction methods and software, computer modeling of the x-rayimaging process, optimization of parameters for limited-angle cone-beamreconstruction problems, digital image processing, machine learning,detection and analysis of abnormalities on 2D and 3D medical images such as CT and tomosynthesisimages

Laboratoryfor Computational Biology & Biophysics, MIT：

The position will focus on application of quantitative image analysis,particle tracking, and trajectory analysis to leading problems in molecular and cellular biology.Applicants should have extensive experience in imageanalysis and machine learning techniques including Hidden Markov Modeling andBayesian Inference, be highly proficient in the use of MATLAB, and havea keen interest to apply as well as further develop computational procedures toaddress critical questions in molecular and cellular biology.

TheComputational Breast Imaging Group (CBIG) of the Radiology Department at theUniversity of Pennsylvania：

Ideal applicants should have a backgroundon biomedical imageanalysis, computer vision, pattern recognition and/or machine learning.Proficiency in quantitative analytical methods and computer programming (e.g.,Matlab, C/C++, ITK) is essential. Experience with medical image analysis (e.g., MRI, CT, X-ray,Ultrasound) or statistical methods and software packages (e.g., SPSS) ispreferable. Additional experience in Imaging Physics is a plus. Applicantsshould demonstrate excellent oral and written communication skills, and theability to work effectively independently and as part of a multidisciplinary team.

中国科学院自动化研究所模式识别国家重点实验室：

现在图像与视频检索、医学图像分割与配准、EEG/MEG信号分析、医学图像多元统计分析、3D医学图像可视化等方向招聘2-3名博士后。

要求：具有如下某个领域研究经历：数学、理论物理、医学影像物理、医学图像处理、脑图像分析、模式识别、机器学习、视频图像分析、计算机科学，并取得相关领域的博士学位；

北大多媒体信息处理研究室招聘博士后：

图像/视频/音频内容理解与检索、图像处理、计算机视觉、模式识别、机器学习、跨媒体检索以及其它相关方向，也欢迎在系统研发上具有突出能力的博士申请。

中国科学院自动化研究所模式识别国家重点实验室2013

http://www.ia.cas.cn/qtgn/tzgg/201303/t20130321_3802577.html