[招聘]马里兰大学College Park多个PhD/Postdoc职位-计算脑科学/大数据建模/仿生AI方向
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Lab & Institution:
The University of Maryland, College Park (UMD or UMCP), was founded in 1856 and is located in the state of Maryland, USA. The university's faculty includes 2 Nobel Prize winners, 4 Pulitzer Prize winners, 58 members of the National Academy of Sciences, and numerous Fulbright Scholars. The A. James Clark School of Engineering at the University of Maryland is ranked among the top 18 engineering schools in the nation, renowned for its innovative education and research programs.
Imaging- and Neuro-computations for Precision Informatics Research (INSPIRE) Lab, led by ece.umd.edu, is launching at the A. James Clark School of Engineering. The lab is anchored at the intersection of data science and brain science. We are dedicated to developing advanced computational models and data science approaches to uncover brain function, neurological disorders, and other biological processes. By leveraging multimodal functional neuroimaging data—including fMRI-BOLD, LFP, optical imaging, and MEG—from animal models, healthy individuals, and patients, we decode complex brain activities and diseases. This integrative approach aims to provide groundbreaking insights that advance both fundamental understanding and translational applications in brain science, informatics, and beyond. For more information, visit inspirelab.site.
Open research directions include but not limited to:
PI: Dr. Nan Xu is an Assistant Professor in the bioe.umd.edu, the ece.umd.edu, and the nacs.umd.edu at the University of Maryland, College Park. With a strong foundation in computational science, her research spans statistical and machine learning, applied mathematics, neuroscience, and various biomedical applications. Her current work focuses on developing advanced computational models and analyses of functional neuroimaging data to gain new insights into brain function, neurological diseases, and broader informatics applications. Nan earned a B.S. in Electrical and Computer Engineering and a B.A. in Mathematics from the University of Rochester in 2011. She completed her M.Sc. (2015) and Ph.D. (2017) in Electrical and Computer Engineering at Cornell University, with minors in Applied Mathematics and Cognitive Neuroscience. Her interdisciplinary postdoctoral experience includes a fellowship in Chemical and Biomolecular Engineering at Georgia Tech (2017-2018), a visiting scientist position at the McGovern Brain Institute at MIT (2022), and a postdoctoral fellowship in Biomedical Engineering at Georgia Tech and Emory University (2019-2024). Her research is currently supported by the prestigious NIH BRAIN Initiative K99/R00 award.
PhD openings: inspirelab.site
Postdoc openings: inspirelab.site
The University of Maryland, College Park (UMD or UMCP), was founded in 1856 and is located in the state of Maryland, USA. The university's faculty includes 2 Nobel Prize winners, 4 Pulitzer Prize winners, 58 members of the National Academy of Sciences, and numerous Fulbright Scholars. The A. James Clark School of Engineering at the University of Maryland is ranked among the top 18 engineering schools in the nation, renowned for its innovative education and research programs.
Imaging- and Neuro-computations for Precision Informatics Research (INSPIRE) Lab, led by ece.umd.edu, is launching at the A. James Clark School of Engineering. The lab is anchored at the intersection of data science and brain science. We are dedicated to developing advanced computational models and data science approaches to uncover brain function, neurological disorders, and other biological processes. By leveraging multimodal functional neuroimaging data—including fMRI-BOLD, LFP, optical imaging, and MEG—from animal models, healthy individuals, and patients, we decode complex brain activities and diseases. This integrative approach aims to provide groundbreaking insights that advance both fundamental understanding and translational applications in brain science, informatics, and beyond. For more information, visit inspirelab.site.
Open research directions include but not limited to:
- Computational Brain Science (e.g., utilizing information theory, graphical models and network science techniques to model functional brain networks.)
- Artificial Intelligence and Data Analytics (bio-inspired AI, AI to predict brain therapy response, statistical learning, etc.)
- Functional Brain Dynamics (statistical/machine learning techniques to analyze the spatiotemporal dynamic patterns of brain measured by multimodal neuroimaging data)
PI: Dr. Nan Xu is an Assistant Professor in the bioe.umd.edu, the ece.umd.edu, and the nacs.umd.edu at the University of Maryland, College Park. With a strong foundation in computational science, her research spans statistical and machine learning, applied mathematics, neuroscience, and various biomedical applications. Her current work focuses on developing advanced computational models and analyses of functional neuroimaging data to gain new insights into brain function, neurological diseases, and broader informatics applications. Nan earned a B.S. in Electrical and Computer Engineering and a B.A. in Mathematics from the University of Rochester in 2011. She completed her M.Sc. (2015) and Ph.D. (2017) in Electrical and Computer Engineering at Cornell University, with minors in Applied Mathematics and Cognitive Neuroscience. Her interdisciplinary postdoctoral experience includes a fellowship in Chemical and Biomolecular Engineering at Georgia Tech (2017-2018), a visiting scientist position at the McGovern Brain Institute at MIT (2022), and a postdoctoral fellowship in Biomedical Engineering at Georgia Tech and Emory University (2019-2024). Her research is currently supported by the prestigious NIH BRAIN Initiative K99/R00 award.
PhD openings: inspirelab.site
Postdoc openings: inspirelab.site
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