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degree in computer science / mathematics /telecommunications / automatics, when starting the PhD. Programming: - Python language (required) - Deep Learning libraries (like TensorFlow, Keras, PyTorch
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, machine learning, and deep learning Good written and oral communication skills Experience in leading research projects Proficiency in basics of programming languages such as Python Self-Motivated and takes
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below: PhD A – Importance of dark carbon fixation in the deep ocean. There is growing evidence that dark carbon fixation contributes to the sustenance of heterotrophic life at great depth. Using 14C and
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cardiovascular MRI, cardiac diffusion tensor imaging, and machine learning or deep learning methods applied to imaging is highly desirable. You will be a collaborative and motivated researcher, capable of working
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and spoken English. Desirable: Experience with photonic/electromagnetics design software. Familiarity with deep learning platforms (e.g. TensorFlow, PyTorch). Funding and eligibility The project is
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beyond the PhD in a research or engineering environment focused on large-scale AI. Experience with geometric deep learning, diffusion architectures, or related frameworks (e.g., OpenFold, AlphaFold2/3
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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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collaboration with the rest of our interdisciplinary team at DTU Construct and Vistacon, particularly the other postdoc position focusing on image analysis using deep learning. [NR1] Dissemination of your
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learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in collaboration
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty