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Field
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-to-confidence set conversion' framework recently proposed by the PI (Principal Investigator). The models of interest include deep neural networks with multiple layers and non-linear activations, extending recent
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skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing to solutions that really make a
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independently. Good communication skills. Fluent in English, both spoken and written. Willing to learn the Dutch language. TU Delft (Delft University of Technology) Working at TU Delft means contributing
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, mathematics, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches for global health challenges. The group’s research spans disease modelling, genomic
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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in one or more of the following research areas is desirable: geometric numerical integration, structure preserving deep learning, stochastic differential equations, generative AI, numerical
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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development, model hosting, deep learning, LLM fine-tuning experience (e.g., with huggingface transformers and parameter-efficient methods such as LoRA/QLoRA), model evaluation experience. (Please briefly
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of cryptographic implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning
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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute