博文
招收博士后: sparse machine learning + bioinformatics
|
最近我的一个合作的实验室（印第安那大学医学院）招收博士后，主要工作是开发基于稀疏性的机器学习/信号处理算法并应用在生物信息学里。具体内容见下。
顺便补充2点
1，人文，氛围
（1）老板是华人，当年交大毕业，Dartmouth College博士毕业。人超级好。每逢节日都邀请实验室的学生们去家里聚餐。经常去外地开会都会买点小玩意回来送给学生。有意向的朋友们尤其是校友请大胆申请，不要有任何担心犹豫。
（2）实验室的氛围非常和谐。每个学生，博士后都非常友好。从来没有发生过勾心斗角的事情。
（3）实验室的条件，设施都很好。最近实验室搬到了新修建的goodman hall，博士后都有自己的大约15平方米的私人办公间。大楼底层是几百万美元修建的健身中心，可以每天工作之后锻炼锻炼。
2，研究工作：这个职位的主要工作是：develop advanced sparse machine learning and bioinformatics strategies for multidimensional brain imaging genetics。生物信息学方面的背景并不是非要求有不可（来了以后可以逐渐了解一点；当然有是最好了），申请这个职位更重要的是要有机器学习，多元统计方面的背景等等。我和他们合作了一年多，我自己也没有任何生物信息学方面的背景，不过还是很成功的和他们合作了许多工作，不少工作已经发表或者正在审稿中。最下面有5篇相关的文章供大家参考。不过我建议最好发email详细询问。
Applications are invited for a Postdoc Position in the Imaging Genomics Lab at the Indiana University School of Medicine (IUSM), funded by an NIH R01 grant. The project is focused on developing advanced sparse machine learning and bioinformatics strategies for multidimensional brain imaging genetics.
Requirements include a Ph.D. in computer science, informatics, statistics, or related disciplines, and a record of academic productivities. Preference will be given to candidates who have experience with advanced techniques for analyzing genome wide array data, complex phenotypic data, and/or systems biology data. A strong interest in integrative analysis of multimodal neuroimaging data, high throughput omics data, and other biomarker data, would be highly desirable, as would solid background in machine learning and bioinformatics, and strong programming experience using Matlab, R, Python, and/or C/C++.
The Imaging Genomics Lab (http://www.iupui.edu/~shenlab/) is affiliated with two multidisciplinary centers at IUSM: (1) Center for Neuroimaging, the hub for all neuroimaging research activities on campus, and (2) Center for Computational Biology and Bioinformatics, the bioinformatics core of IUSM. There is an excellent set of critical resources at IUSM, including (1) experts from neuroscience, imaging science, computer science, genetics, informatics, and statistics, (2) state-of-the-art imaging facilities, and (3) large scale computer systems and advanced software tools. The successful candidate will benefit from mentorship of a diverse research team and will be exposed to cutting-edge technology by collaborating on various genomic and imaging projects.
Interested candidates should email their CV, selected reprints and a list of three references to: Li Shen at shenli@iupui.edu
Indiana University is an AA/EOE employer, M/F/D.
The approaches will be similar to those proposed in the following papers.
[1] Vounou M, Janousova E., Wolz R., Stein J. Thompson P., Rueckert D. and Montana G. (2011) Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. NeuroImage, 60(1):700-716
[2] T. Ge, J. Feng, D.P. Hibar, P.M. Thompson, and T.E. Nichols. Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures. NeuroImage, 63(2): 858-873, 2012.
[3] Witten DM, Tibshirani R, and T Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3): 515-534.
We will be dealing with data similar to those in the following papers.
[4] Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI,Stevens MC,Calhoun VD, Glahn DC, Shen L, Risacher SL, Saykin AJ, Pearlson GD (2012) A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. Neuroimage, 60(3):1608-1621. doi:10.1016/j.neuroimage.2011.12.076
[5] Shen L, Kim S, Risacher SL, Nho K, Swaminathan S, West JD, Foroud TM, Pankratz ND, Moore JH, Sloan CD, Huentelman MJ, Craig DW, DeChairo BM, Potkin SG, Jack CR, Weiner MW, Saykin AJ, and ADNI. Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort. NeuroImage, 53:1051-1063, 2010. http://dx.doi.org/10.1016/j.neuroimage.2010.01.042.
https://blog.sciencenet.cn/blog-765184-639722.html
上一篇：写毕业论文真是个体力活
下一篇：一小时的答辩presentation简直就是个不可能完成的任务
顺便补充2点
1，人文，氛围
（1）老板是华人，当年交大毕业，Dartmouth College博士毕业。人超级好。每逢节日都邀请实验室的学生们去家里聚餐。经常去外地开会都会买点小玩意回来送给学生。有意向的朋友们尤其是校友请大胆申请，不要有任何担心犹豫。
（2）实验室的氛围非常和谐。每个学生，博士后都非常友好。从来没有发生过勾心斗角的事情。
（3）实验室的条件，设施都很好。最近实验室搬到了新修建的goodman hall，博士后都有自己的大约15平方米的私人办公间。大楼底层是几百万美元修建的健身中心，可以每天工作之后锻炼锻炼。
2，研究工作：这个职位的主要工作是：develop advanced sparse machine learning and bioinformatics strategies for multidimensional brain imaging genetics。生物信息学方面的背景并不是非要求有不可（来了以后可以逐渐了解一点；当然有是最好了），申请这个职位更重要的是要有机器学习，多元统计方面的背景等等。我和他们合作了一年多，我自己也没有任何生物信息学方面的背景，不过还是很成功的和他们合作了许多工作，不少工作已经发表或者正在审稿中。最下面有5篇相关的文章供大家参考。不过我建议最好发email详细询问。
Applications are invited for a Postdoc Position in the Imaging Genomics Lab at the Indiana University School of Medicine (IUSM), funded by an NIH R01 grant. The project is focused on developing advanced sparse machine learning and bioinformatics strategies for multidimensional brain imaging genetics.
Requirements include a Ph.D. in computer science, informatics, statistics, or related disciplines, and a record of academic productivities. Preference will be given to candidates who have experience with advanced techniques for analyzing genome wide array data, complex phenotypic data, and/or systems biology data. A strong interest in integrative analysis of multimodal neuroimaging data, high throughput omics data, and other biomarker data, would be highly desirable, as would solid background in machine learning and bioinformatics, and strong programming experience using Matlab, R, Python, and/or C/C++.
The Imaging Genomics Lab (http://www.iupui.edu/~shenlab/) is affiliated with two multidisciplinary centers at IUSM: (1) Center for Neuroimaging, the hub for all neuroimaging research activities on campus, and (2) Center for Computational Biology and Bioinformatics, the bioinformatics core of IUSM. There is an excellent set of critical resources at IUSM, including (1) experts from neuroscience, imaging science, computer science, genetics, informatics, and statistics, (2) state-of-the-art imaging facilities, and (3) large scale computer systems and advanced software tools. The successful candidate will benefit from mentorship of a diverse research team and will be exposed to cutting-edge technology by collaborating on various genomic and imaging projects.
Interested candidates should email their CV, selected reprints and a list of three references to: Li Shen at shenli@iupui.edu
Indiana University is an AA/EOE employer, M/F/D.
The approaches will be similar to those proposed in the following papers.
[1] Vounou M, Janousova E., Wolz R., Stein J. Thompson P., Rueckert D. and Montana G. (2011) Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. NeuroImage, 60(1):700-716
[2] T. Ge, J. Feng, D.P. Hibar, P.M. Thompson, and T.E. Nichols. Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures. NeuroImage, 63(2): 858-873, 2012.
[3] Witten DM, Tibshirani R, and T Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3): 515-534.
We will be dealing with data similar to those in the following papers.
[4] Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI,Stevens MC,Calhoun VD, Glahn DC, Shen L, Risacher SL, Saykin AJ, Pearlson GD (2012) A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI cohort. Neuroimage, 60(3):1608-1621. doi:10.1016/j.neuroimage.2011.12.076
[5] Shen L, Kim S, Risacher SL, Nho K, Swaminathan S, West JD, Foroud TM, Pankratz ND, Moore JH, Sloan CD, Huentelman MJ, Craig DW, DeChairo BM, Potkin SG, Jack CR, Weiner MW, Saykin AJ, and ADNI. Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort. NeuroImage, 53:1051-1063, 2010. http://dx.doi.org/10.1016/j.neuroimage.2010.01.042.
https://blog.sciencenet.cn/blog-765184-639722.html
上一篇：写毕业论文真是个体力活
下一篇：一小时的答辩presentation简直就是个不可能完成的任务
