Kidsearlylearningcenters
Postdoctoral Fellow – Machine Learning, Harvard Medical School & MGH, Boston, MA
Kidsearlylearningcenters, Boston, Massachusetts, us, 02298
Postdoctoral Fellow – Machine Learning:
We are seeking talented and driven postdoctoral fellows with experience in machine learning for image analysis to join the computational team of the Center for Large-Scale Imaging of Neural Circuits (LINC) at Harvard Medical School and Massachusetts General Hospital. The LINC project is a multi-disciplinary initiative involving eight prestigious institutions aimed at developing novel technologies for imaging brain connections down to the microscopic scale. Summary Table:
Title:
Postdoctoral Fellow – Machine Learning for Imaging Neural Circuits Designation:
Postdoctoral Research Fellow Research Area:
Machine Learning for Image Analysis in Neuroscience Location:
Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School & MGH, Boston, MA Eligibility:
Ph.D. in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Math, or related field. Background in computer vision/machine learning. Experience with microscopy or diffusion MRI data is a plus. Creativity, initiative, proven ability to publish, and excellent communication skills. Job Description:
Develop ML algorithms for analyzing microscopy and MRI data, reconstruct neural circuits. Join the LINC project to develop tools for analyzing data from microscopy and MRI teams. Potential projects include: Microscopy Data Analysis:
Develop algorithms for high-throughput, automated analysis of optical and X-ray microscopy datasets, including cross-modal registration and axon segmentation. Fiber Architecture Inference:
Create models trained on ground-truth microscopy and diffusion MRI data to infer fiber architectures directly from diffusion MRI. Multi-scale Tractography:
Develop algorithms utilizing data from multiple modalities and scales to enhance reconstruction of neural connections, both ex vivo and in vivo. The position offers an opportunity to collaborate with leading experts at the Martinos Center and be part of Boston’s vibrant neuroimaging community. The roles are full-time with benefits, starting immediately. How to Apply:
Submit the following documents via email to Dr. Anastasia Yendiki at ayendiki [at] mgh.harvard.edu: CV Contact information for two references Cover letter describing research background, interests, and professional goals Last Date to Apply:
Open until filled.
#J-18808-Ljbffr
We are seeking talented and driven postdoctoral fellows with experience in machine learning for image analysis to join the computational team of the Center for Large-Scale Imaging of Neural Circuits (LINC) at Harvard Medical School and Massachusetts General Hospital. The LINC project is a multi-disciplinary initiative involving eight prestigious institutions aimed at developing novel technologies for imaging brain connections down to the microscopic scale. Summary Table:
Title:
Postdoctoral Fellow – Machine Learning for Imaging Neural Circuits Designation:
Postdoctoral Research Fellow Research Area:
Machine Learning for Image Analysis in Neuroscience Location:
Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School & MGH, Boston, MA Eligibility:
Ph.D. in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Math, or related field. Background in computer vision/machine learning. Experience with microscopy or diffusion MRI data is a plus. Creativity, initiative, proven ability to publish, and excellent communication skills. Job Description:
Develop ML algorithms for analyzing microscopy and MRI data, reconstruct neural circuits. Join the LINC project to develop tools for analyzing data from microscopy and MRI teams. Potential projects include: Microscopy Data Analysis:
Develop algorithms for high-throughput, automated analysis of optical and X-ray microscopy datasets, including cross-modal registration and axon segmentation. Fiber Architecture Inference:
Create models trained on ground-truth microscopy and diffusion MRI data to infer fiber architectures directly from diffusion MRI. Multi-scale Tractography:
Develop algorithms utilizing data from multiple modalities and scales to enhance reconstruction of neural connections, both ex vivo and in vivo. The position offers an opportunity to collaborate with leading experts at the Martinos Center and be part of Boston’s vibrant neuroimaging community. The roles are full-time with benefits, starting immediately. How to Apply:
Submit the following documents via email to Dr. Anastasia Yendiki at ayendiki [at] mgh.harvard.edu: CV Contact information for two references Cover letter describing research background, interests, and professional goals Last Date to Apply:
Open until filled.
#J-18808-Ljbffr