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TECNIOSPRING - POST DOC - ARTIFICIAL INTELLIGENCE FOR ENDOLUMINAL IMAGE CLASSIFICATION

Descripción de la oferta de empleo

TECNIOspring PLUS, ACCIÓ's scholarship program, provides financial support to individual mobility proposals submitted by experienced researchers in relation to a host entity.
Fellows are offered  2-year  employment contracts in order to develop research projects applied to the host entity of their choice.
INSTITUTION.
DataScience@UB is a R&D group of the Universitat de Barcelona that works on the challenges originated by the massive generation of data in different application fileds, and we do so from the technological, scientific and social point of view.
We are specialists in data science, a key discipline in digital transformation that involves generating and interpreting information on a large scale.
PROJECT REVIEW.
This is an Outgoing+Return project in collaboration with CorporateHealth International, the Hospital General de la Vall d'Hebron and the DataScience group at the Universitat de Barcelona.
During the first year of the project, the candidate will work with the CorporateHealth team in Scotland and during the second year stay at the University of Barcelona The main task of the researcher be to develop Artificial Intelligence/Deep Learning solutions to help physicians in analyzing capsule endoscopy videos and creating a diagnosis.
The collaboration has already achieved substantial results through joint work since .
The researcher will build upon that science and technology to make further advances.
  The research is highly relevant in the medical progress towards eradicating colorectal cancer.
Currently, only a visual inspection of the bowel can accurately predict the risk for cancer and direct which preventive or therapeutic measures have to be taken.
However, the predominantly used optical colonoscopy is invasive and highly resource intense.
While wireless capsule endoscopy is much more patient-friendly, easy to scale, but requires hours of expert video analysis.
The project addresses this challenge by developing a more automated solution using AI.
  Therefore, the research focuses on 2 tightly connected domains.
Creating tools and early-stage neural networks to support the preparation of data sets for machine learning Creating neural networks and related user interfaces to support the experts in their process of diagnosing patients Topics like uncertainty DL models, explainable DL and domain adaptation will be the core of the research within the two years grant Check out this video.
https://www.
outube.
om/watch?v=y3huP4FPiyA
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Detalles de la oferta

Empresa
  • University of Barcelona
Localidad
Dirección
  • Sin especificar - Sin especificar
Salario
  • Sin especificar
Fecha de publicación
  • 15/10/2020
Fecha de expiración
  • 13/01/2021
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