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Field
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. ESSENTIAL REQUIREMENTS A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas. Documented expertise in: Machine/Deep Learning, and possibly Computer
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the measurement instrument in close collaboration with our industrial partner, Veridis Technologies. An ideal candidate has experience in vibrational spectroscopy and spectral processing. Expertise in deep learning
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 days ago
pipeline, building on existing deep learning models in meteorology and climate science Your Profile PhD in computational science, mathematics, physics, or a related subject Experience with machine-learning
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specifically detailing your interest in glioblastoma and deep learning Two reference letters For more information:stein.aerts@kuleuven.be Where to apply Website https://jobs.vib.be/j/130090/postdoc-position-deep
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 7 days ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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focuses on single-cell genomics, biotechnology, and bioinformatics. The project involves transcriptomic and genomic profiling of single microbes. The post-doc will work on machine and deep learning methods
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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highly stimulating environment that engages the best and brightest faculty and students to conduct deep and impactful research. Our faculty's research expertise and strengths cover several key
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closely related quantitative discipline. Demonstrated experience with large-scale deep learning models and modern ML frameworks (e.g., PyTorch, JAX, Transformers), including training, fine-tuning
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. The primary objective is to develop computational methods, using deep learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted