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8 months ago
The Faculty of Science for its new lab on AI for Medical Imaging (AIM lab) at the University of Amsterdam is inviting applications for six PhD candidates. The research lab will be focused on medical image analysis by machine learning, covering active scientific topics of broad interest, including both methods and applications.
PhD projects:
- Medical Image Denoising and Enhancement
- Multi-Task Learning for Medical Image Analysis and Data Mining
- Shape Analysis for Object Segmentation and Structure Analysis
- Early Diagnosis of Alzheimer’s Disease with Deep Neural Networks
- Cancer Diagnosis by Jointly Learning from Medical Images and Health Records
- Automated Report Generation from Radiology Images
Requirements:
- A Master’s degree in Artificial Intelligence, Computer Science, or related field;
- A strong background in computer vision and machine learning;
- Excellent programming skills, preferably in Python and C/C++;
- solid mathematics foundations, especially statistics, calculus and linear algebra;
- Applicant must be highly motivated and creative;
- Strong communication, presentation and writing skills and excellent command of English.
Applications:
Apply online and applications should include:
- a motivation letter that motivates his/her choice for this position, and in particular, for which of the research projects;
- CV, including list of publications if applicable;
- a link to the Master’s thesis;
- a complete record of Bachelor and Master courses (including grades and explanation of grading system);
- a list of projects that candidate have worked on (with brief descriptions of your contributions, max 2 pages);
- The names and contact addresses of at least two academic references (please do not include any recommendation letters).
—————–Quick Overview————- | |
Organization | University of Amsterdam |
Country | Netherlands |
Fellowship Level | Doctoral |
Subject areas | Artificial Intelligence, Computer Science |
Fellowship amount | €2,325 to €2,972 gross per month |
Eligibility | Varies |
Deadline | 1 December 2019 |
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