Ghassan Hamarneh
 Professor
 School of Computing Science
 Faculty of Applied Science
 Simon Fraser University

 ACM Senior Member & IEEE Senior Member
 BRC RAMP NeuroDevNet NeuroScience
 CDIRE BIONF MICCAI BCNI CFRI PHP

 
Medical Image Analysis Lab

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PhD Positions /  Postdoctoral fellowship in Medical Image Analysis at Simon Fraser University, BC, Canada

PhD Position
(Updated Dec. 13, 2015)

A fully-funded PhD position is available for a student to work on image analysis for neurosurgery. The project is a collaboration between the Medical Image Analysis Lab at Simon Fraser University and Neurosurgeons at the Vancouver General Hospital in Vancouver, Canada. The student will apply and develop image segmentation, registration and machine learning algorithms and tools to enhance the neurosurgeons' workflow and improve or predict the patientís treatment or outcome. An ideal candidate has recently completed a masters degree in machine learning, computer vision, image processing or related areas, is preferably familiar with 3D medical image analysis methods and tools (segmentation, registration, ITK), is skillful in computational and mathematical techniques (high dimensional data analysis, graph theory, optimization) and programming (C/C++, Python, MATLAB), and is eager to learn and apply his/her skills to solve important clinical problems.

Interested student should send an email (subject: neurosurgery image analysis phd) with their CV to Prof. Ghassan Hamarneh <hamarneh@sfu.ca>.

Postdoctoral fellowship:

(Updated Feb. 13, 2014):

The Medical Image Analysis Lab at Simon Fraser University has an opening for a postdoctoral fellow, starting as early as Mar. 1st, 2015, to carry out world-class research in the area of multi-modal medical image analysis. The successful candidate will complement a collaborative team of scientists, graduate students, and other postdocs in Vancouver, Canada, in the areas of molecular oncology, genomics, and medical image reconstruction and analysis. The focus will be on multi-modal CT/PET segmentation to measure tumour burden and it's relation to cancer genomics. The postdoc will join SFU's School of Computing Science, ranked one of the top 50 CS schools worldwide, while working closely with the BC Cancer Agency, Vancouver General Hospital, and other UBC team members. Candidates are expected to have published in top venues (e.g. IEEE TMI, MedIA, MICCAI, IPMI, ICCV, CVPR or similar) during the past few years. Experience in 3D medical image processing, segmentation and registration, machine learning, and optimization are essential, as well as excellent programming skills (e.g. C/C++, MATLAB, ITK, Python) and scientific writing abilities.

If you are interested in this opportunity and possess the skills described above,
send an email with your CV attached and listing the names of 3 references to Prof. Ghassan Hamarneh: hamarneh@sfu.ca with the subject: SFU multi-modal segmentation postdoc.

Links:
- Postdoc information from SFU: http://www.sfu.ca/dean-gradstudies/postdocs.html

PhD Position:

(Updated Feb. 13, 2014):

The Medical Image Analysis Lab at Simon Fraser University has fully-funded PhD positions to carry out world-class research in the area of multi-modal medical image analysis. The successful candidate will be part of a collaborative team of scientists, graduate students, and postdocs in Vancouver, Canada, in the areas of molecular oncology, genomics, and medical image reconstruction and analysis. The focus will be on multi-modal CT/PET segmentation to measure tumour burden and it's relation to cancer genomics. The PhD student will join SFU's School of Computing Science, ranked one of the top 50 CS schools worldwide, while working closely with the BC Cancer Agency, Vancouver General Hospital, and other UBC team members. Ideal candidates are those who hold BSc or MSc degrees in computer science, engineering, applied math. or similar disciplines, have done their MSc theses (or BSc theses/projects) in image processing, computer vision, machine learning, and optimization (or have strong interests in these topics and their applications in medicine), have excellent programming skills (e.g. in C/C++, MATLAB, Python), and excellent written and spoken English.

Interested? Please complete the form here.

 
 
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