[4eyes] FW: POST-DOCTORAL SCHOLARSHIP ON MEDICAL IMAGING - USP - SAO PAULO - BRAZIL

[Matthew Turk]

FYI
 
From: Roberto Marcondes Cesar Junior <rmcesar at usp.br> 
Sent: Thursday, December 6, 2018 9:20 AM
To: Roberto M Cesar Junior <cesar at vision.ime.usp.br>
Subject: POST-DOCTORAL SCHOLARSHIP ON MEDICAL IMAGING - USP - SAO PAULO - BRAZIL
 
Dear all,
 
Could you please help me to disseminate the opportunity below? Thanks a lot!
 
Regards,
 
Roberto
 
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JOB POSITION - POST-DOCTORAL SCHOLARSHIP ON MEDICAL IMAGING - USP - SAO PAULO - BRAZIL
 
Knowledge area: Computer Science / Image Analysis
Project Title: Spatio-temporal analysis of paediatric magnetic resonance images 
Specific area : Medical Imaging
Job start: May 2019
Supervisor : Roberto M. Cesar Jr. (https://www.ime.usp.br/~cesar/)
Institution: Data Science Group (http://escience.ime.usp.br/)  - Institute of Mathematics and Statistics of the University of Sao Paulo  - USP
Address: Rua do Matao, 1010, Cidade Universitaria, Sao Paulo, Brasil.
Deadline for application: March 20th 2019
Inscription e-mail: rmcesar at usp.br <mailto:rmcesar at usp.br> 
Description of the project
 
Medical imaging require the development of methods to improve accuracy in the image analysis results. Advances in medical image analysis provide such tools, but there is still an important gap regarding paediatric brain imaging, even though there is an increasing medical demand. This project aims at contributing to fill this gap, focusing on brain magnetic resonance imaging (MRI) of infants, newborns and premature babies, which raise specific issues due to the particular grey/white matter contrast related to the physiological myelination process, the very fast but not continuously observed evolution of the brain structures and possible pathologies, and the high intra-and inter-subjects variability.
 
One of these issues is that the data is typically noisy, ambiguous, scarce in nature and sparse in time. In turn, expert medical knowledge is available, but is prone to change and evolution. From this point of view the project tackles one of the very cutting edge questions in data analysis, i.e. how to extract and understand meaningful patterns where the data is scarce but expert knowledge, continuously enriched, is available. We propose to develop structural representations of knowledge and image information in the form of graphs and hypergraphs, which will be exploited to guide spatio-temporal image understanding (segmentation, recognition, quantification, comparison over time, description of image content and evolution).
 
The aim is to develop computational methods to support diagnosis, pathology analysis and patients follow-up. Applications will include the analysis of hyperintensities on the white matter, the volumetry of corpus callosum and its evolution, and neuro-oncology with the study of the influence of tumors on surrounding structures over time.
 
 
About the institution
The University of Sao Paulo is one of the the best ranked Universities in Latin America, being considered one of country's more prestigious educational institutions. The Data Science Group at IME-USP is a traditional machine learning research working on the field for more than 20 years with strong international collaboration.
 
About the project
The candidate will work on two connected projects co-funded by FAPESP (Sao Paulo Research Foundation) and ANR (Agence Nationale de Recherche - France). The  FAPESP-ANR joint project is a collaboration that includes the following Institutions: USP (Institute of Mathematics and Statistics and School of Medicine), Albert Einstein Hospital - SP, ParisTech, Universite Dauphine and Faculte de Medicine Paris Sud . The project focuses in the development of computational tools for processing of MRI images and their integration with biological data. The project involves specialists in medical image analysis, structural knowledge representation and paediatric neuro-imaging. 
 
The selected candidate will be funded by a FAPESP fellowship with the one of the following conditions:  Initial funding of 2 years (being possibly extended up to 4 years based on performance), fellowship R$ 90K per year  (approx. US$ 24K / year) plus overhead for travel expenses  such as attending to conferences.  More information is available at http://www.fapesp.br/en/5427 The grant may also cover expenses for moving to Sao Paulo/Brasil (including flight tickets).
 
The candidate may also apply for an extra period (4 months to 1 year) to do part of the research at the ParisTech, Universite Dauphine or Faculte de Medicine Paris Sud (FAPESP BEPE fellowship) as part of the grant (not included in the aforementioned 4 years).
 
 
Required Skills
PhD degree with strong background in mathematical modelling and programming (e.g. Computer Science, Engineering, Physics, Math). Research experience and publications in one or more of the following areas: image processing, computer vision, pattern recognition, machine learning, 

Oral and written communication skills (English).
Application details
Please send the following documents to rmcesar at usp.br <mailto:rmcesar at usp.br>  :
 
- CV
- Summary of doctoral thesis and other relevant works
- Two recommendation letters from former supervisors or professors of courses you took.
 


 
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Roberto M. Cesar-Jr
Department of Computer Science - IME - USP - Brazil
CV, publications, opportunities for students: http://www.ime.usp.br/~cesar/
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