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Field
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning
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-modality models Knowledge in deep learning optimization, such pruning and quantization Strong academic writing skill Personal characteristics To complete a doctoral degree (PhD), it is important that you are
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into the mechanisms governing hydrogen-induced degradation and failure of circular steels. As a PhD researcher, you will: Perform advanced 3D microstructural characterization of circular steels, focusing on segregation
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” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. The most
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experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team
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Join TU Delft and help design hydrogen-resistant steels for a sustainable energy future. As a PhD researcher, you will unravel the atomic-scale mechanisms of hydrogen embrittlement in
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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reliable hydrogen-resistant circular steels. In this role, you will develop fundamental insights into the mechanisms governing hydrogen-induced degradation and failure of circular steels. As a PhD researcher
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) Recognised Researcher (R2) Positions PhD Positions Application Deadline 28 Sep 2026 - 12:00 (Europe/Copenhagen) Country Denmark Type of Contract Temporary Job Status Full-time Is the job funded through the EU