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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical
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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible
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, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory Familiar with machine learning and deep learning Programming experience (Python or Julia) and their
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the subsequent years, you will combine these insights with predictive modelling and select, train, and validate process-based or deep-learning fire propagation models using a.o. detailed information about
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
immunology with deep focus on T cells and Treg biology Hands-on experience with in vivo mouse models (FELASA certification is a strong plus) Practical experience in flow cytometry (FACS), including protocol
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holders. XJTLU offers our undergraduates and postgraduates over 100 programmes with a diverse spectrum of courses. With a focus on innovative learning and teaching, and research, XJTLU draws
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the mechanobiology of native and engineered tissues, with a current focus on cardiovascular applications, using integrated computational and experimental methods. The group focuses on developing a deep understanding
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candidate would be required to live in or relocate to Southeastern Michigan. Follow the link below to learn more about the projects and research conducted at UMTRI: https://www.umtri.umich.edu/research
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, TensorFlow, or JAX) Experience with photonic design techniques and global optimisation algorithms (Genetic Algorithms, Particle Swarm, Gradient Descent) Experience implementing deep learning architectures