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. Through continuous structural monitoring systems Through continuous structural monitoring systems and artificial intelligence algorithms (machine and deep learning, hybrid physical-data driven methods
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Part-Time Lecturer for EE7207 Neural Networks and Deep Learning The School of Electrical and Electronic Engineering (EEE) at Nanyang Technological University, Singapore, invites qualified candidates
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at Forschungszentrum Jülich, in close collaboration with bioimage analysis partners at Karlsruhe Institute of Technology. Your tasks in detail: Develop and extend deep-learning–based segmentation, classification and
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been established. This position will focus on the further development of various, machine learning and deep learning models to study molecular mechanisms and cellular phenotypes caused by the etiology
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Scientist / Scientific assistant – Tree species detection using deep-learning Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 3 days ago
programming skills in languages such as Python, C/C++ and CUDA # Familiarity with modern deep learning frameworks like Tensorflow 2.x.x, PyTorch # Mandatory experience with High-Performance Computing (HPC
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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
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/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
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to coordinate procedures and teaching resources Part time (0.8FTE), fixed-term (2 years) role based in Launceston About the opportunity Support quality learning and teaching to enhance the student experience and
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CORE A*/A conference paper. We invite applications for a postdoctoral position focused on the development of predictive models for clinical outcomes following Deep Brain Stimulation (DBS) in Parkinson’s