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(optimal) solutions—with subsymbolic approaches such as deep learning and reinforcement learning to reduce the complexity of knowledge acquisition and search for solutions. Therefore, this project is closely
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synchronous sessions, workshops, practical sessions, project supervision, clinics, tutorials, seminars, and the creation of blended learning materials. Context The Department of Computer Science
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learning and deep learning Excellent programming skills in Python Practical experience with PyTorch (preferred) and/or with TensorFlow, scikit-learn, and GitHub Experience with scientific experimentation and
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, training, product/platform ownership, or digital transformation roles. Incumbent must have the ability to blend front-facing, executive level consulting skills with deep technical knowledge to identify
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date specified in AP Recruit to learn whether the department is currently reviewing applications for a specific position. If there is no future review date specified, your application may not be
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
deep learning (x/f/d/m) Background With the project Deepcloud, we will leverage the machine-learning revolution to understand clouds and their role in the climate system. We aim to train a deep learning
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demonstrated track record in protein structure modelling methods, with hands‑on experience in protein or biologics design and engineering. Hands‑on experience with common machine learning / deep learning
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data (PET, CT, Magnetic Resonance Imaging with Late Gadolinium Enhancement – MRI-LGE) and clinical variables. The approach encompasses unsupervised multimodal registration, three-dimensional deep
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, combined with a deep understanding of pedagogy and best practices for student success, is essential. Experience in programs that support student retention, such as first-year experience (FYE) programs or a