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Let’s shape the future - University of Antwerp
The University of Antwerp is a dynamic, forward-thinking, European university. We offer an innovative academic education to more than 20000 students, conduct pioneering scientific research and play an important service-providing role in society. We are one of the largest, most international and most innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push back boundaries and set a course for the future – a future that you can help to shape.
The Vision Lab of the Department of Physics in the Faculty of Sciences is looking for a full-time (100%) doctoral scholarship holder in the field of Processing and analysis of magnetic resonance images using machine and deep learning.
This position is part of the ERC Consolidator project “A data-driven approach to microstructure imaging” (ADAMI), funded by the European Union. ADAMI is a highly interdisciplinary project that combines insights from physics/engineering (magnetic resonance imaging (MRI) and light-sheet microscopy), biological and medical sciences (tissue microstructure, immunostaining, and neuroscience), and computer science (data analysis, image processing, machine learning, and artificial intelligence) to achieve a breakthrough in microstructure imaging with MRI.
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The University of Antwerp received the European Commission’s HR Excellence in Research Award for its HR policy. We are a sustainable, family-friendly organisation which invests in its employees’ growth. We encourage diversity and attach great importance to an inclusive working environment and equal opportunities, regardless of gender identity, disability, race, ethnicity, religion or belief, sexual orientation or age. We encourage people from diverse backgrounds and with diverse characteristics to apply.
The University of Antwerp is characterised by its high standards in education, internationally competitive research and entrepreneurial approach.
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