Ongeveer 13 uur geleden - Technische Universiteit Eindhoven (TU/e) - Eindhoven
MotivationFibre optics are critical infrastructure for society because they carry nearly all the global Internet traffic. For a long time, optical fibre system…
One million men receive a prostate cancer diagnosis, and three hundred thousand die from prostate cancer each year worldwide. Magnetic Resonance Imaging (MRI) represents a major breakthrough by accurately detecting clinically significant prostate cancers at ...
One million men receive a prostate cancer diagnosis, and three hundred thousand die from prostate cancer each year worldwide. Magnetic Resonance Imaging (MRI) represents a major breakthrough by accurately detecting clinically significant prostate cancers at an early, potentially more curable stage. The same MRI can also be used for better treatment targeting and for avoiding unnecessary systematic biopsies. As a result, the demand for Prostate MRI is rapidly increasing. Unfortunately, reading these multiparametric MRI (mpMRI) exams is difficult and requires substantial expertise. Computers can potentially extract more information from mpMRI, more reliably, and more accurately than human readers. Artificial Intelligence is becoming indispensable in helping improve mpMRI diagnostic performance.
This project aims to research computer-aided diagnostic systems that will demonstrably help clinicians to get the best possible prostate cancer diagnosis from mpMRI. The research includes quantitative imaging biomarkers, and multivariate analysis using an extensive MRI database with datasets of expert annotations. State-of-the-art predictive models will be continuously evaluated and implemented in a clinical prototype for validation and feedback. Results will be presented at scientific meetings and published in journals.
We will closely work with the Diagnostic Image Analysis Group (DIAG), a research division of the Department of Radiology and Nuclear Medicine of the Radboud University Medical Center Nijmegen, which has an extensive experience in the field of various medical image analysis topics.
You should be a creative and enthusiastic researcher with an MSc degree in Computer Science, Data Science, Physics, Engineering or Biomedical Sciences or similar, with a clear interest in machine learning, radiomics, image analysis and an affinity with medical applications. Good communication skills and expertise in software development, preferably in Python/C++, are essential. Experience with artificial intelligence is a pre. The research should result in a Ph.D. thesis.
The UMCG has a preventive Hepatitis B policy. The UMCG can provide you with the vaccination, should it be required for your position.
Radiology, Nuclear Medicine & Medical Imaging
The University Medical Center Groningen (UMCG) is one of the largest hospitals in the Netherlands and the largest employer in the Northern Netherlands. In addition to providing clinical care, there is much focus on the core research, training and education. The Department of Radiology, Nuclear Medicine and Molecular Imaging is part of the UMCG. It has well-established structural international research collaborations with academic partners.
At least as important as a pleasant working environment is a pleasant living environment. Groningen is a thriving university city set in quiet, spacious surroundings.
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