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Hiring Unit:
The Department of Bioengineering- Reznikov Laboratory
Position Summary:
Project title: Upsampling of low-resolution/large-volume 3D tomographic images using generative adversarial neural networks applied to biological anthropology, medical imaging and evolutionary biology.
The aim of this project is to design and validate an open-ended upsampling algorithm using 3D images of historical (ancient mummies), clinical (dental cone-beam X-ray computed tomography) and basic science (bird eggshell) samples. Unique to this project is the availability of original multi-scale 3D image sets that span multiple resolution/volume scales, and which can be accurately superimposed (registered) in 3D, and can be expertly segmented (having meaningful features identified and assigned to the target class on a voxel basis). By applying GAN-CNN to a low-resolution/large-volume image using a high-resolution/low-volume image as ground truth, we will achieve 3D image upsampling ×n . To circumvent the inevitable increase of the data size (×n 3) we will implement a parallel segmentation algorithm that reduces voxel depth, because the ultimate objective is the segmentation of upsampled images.
Qualifications:
- PhD degree in Computer Science or related disciplines
- Knowledge in computer vision-related topics including but not limited to 3D image segmentation
- In-depth knowledge of modern deep learning techniques for image processing
- Familiarity with one of the deep learning frameworks (Tensorflow, Pytorch)
- Understanding of micro-computed tomography is advantageous
- Strong Python, Matlab, and C++ experience
- Strong presentation, communication and writing skills
Annual Salary:
(AMURE Post-Doctoral Fellow Researcher) $34,611.00
Hours per Week:
35 (Full time)
Location:
McConnell Eng. Bldg.
Supervisor:
Assistant Professor
Position Start Date:
2022-06-20
Position End Date:
2023-07-31
Deadline to Apply:
2022-06-25
McGill University hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and encourages members of designated groups to self-identify. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, [email protected] .
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