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accordance with a set individual study plan. The focus will be on performing research to optimize and test DBTMI by combining state-of-the-art computer simulations, physical experiments, and clinical studies
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by combining state-of-the-art computer simulations, physical experiments, and clinical studies in radiology departments at the hospitals in the region. You will work in a multi-disciplinary team and
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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look forward to receiving your application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with
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dynamics and heat transfer research. Programming skills in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability
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for multimodal machine learning, combining large-scale image data with molecular profiling and clinical data. This includes, for instance, research on deep learning-based image analysis and data assimilation
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, pharmacology, inflammation, cancer and neurobiology. We also teach students studying at various programs and independent courses in cell biology, physiology, neurobiology, anatomy and histology
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dynamics and heat transfer research. Programming skills in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability
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of visualization and multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits