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Description Are you curious how Deep Learning and Online Learning can be effectively combined to create new learning paradigms? Job description Online learning algorithms achieve robustness often at the expense
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). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with Reinforcement Learning, Deep Learning and/or Explainable AI, demonstrated for example through
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across both surface and subsurface layers. This includes constructing robust feature extraction pipelines, attention-based fusion architectures, and deep learning models that accurately characterize cracks
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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, including bioinformatics. You translate molecular insights into clinical applications and contribute to scientific publications and presentations. Where to apply Website https://www.academictransfer.com/en
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cardiovascular applications, using integrated computational and experimental methods. The group focuses on developing a deep understanding of how mechanical stimulation regulates growth and remodeling, with
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skills (Python) and knowledge of deep-learning frameworks (PyTorch) are expected. A certain affinity towards turning complex concepts into real-world practice is desired. The successful candidate is
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MERLN Institute at Maastricht University. What if you could teach a biomaterial to heal bone by delivering the molecular instructions directly to cells? This PhD project explores exactly that question
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convergent disease pathways and therapeutic targets. By combining stem cell biology, tissue engineering, gene editing, and deep phenotyping, you help bridge the gap between genetic discovery and functional
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topics broadly cover how companies build and retain sustained competitive advantage in the face of current business- and societal challenges. Overall, we are looking for a candidate who is eager to learn