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Field
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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Conference on Neural Networks (IJCNN), pages 1–10, July 2022. doi: 10.1109/IJCNN55064. 2022.9892277. URL https://ieeexplore.ieee.org/document/9892277/?arnumber= 9892277. G. Bellec, D. Salaj, A. Subramoney, R
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staff position within a Research Infrastructure? No Offer Description Title: “Synthetic Dataset Generation Technique to Optimize Neural Network Training for Seismic Data Prediction” Research Area
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The Leibniz Institute for Neurobiology (LIN) is an internationally recognized neuroscience research institute dedicated to understanding the neural mechanisms of learning and memory across
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involve the adoption of various neural network architectures, including Convolutional, Artificial, and Spiking Neural Networks and their embedding into electronic platforms such as ARM-CORTEX, RISC-V and
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Los Alamos has been rated #3 in the Best Counties to Live in the USA. Apply Now https://lanl.jobs/search/jobdetails/sparse-neural-network-design-post-doctoral-research-associates/e80bfca8-271e-4be8-b205
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in a research environment a plus General languages (preferred): C++, Python, MATLAB CUDA (strongly preferred) Machine learning knowledge. e.g. logistic regression, SVM, neural network models Basic
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postdoctoral fellowship at ENS Lyon in the field of machine learning. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE
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research centre dedicated to understanding normal and pathological brain function and developing new diagnostic and therapeutic approaches. Website: https://neurosciences.univ-grenoble-alpes.fr You will be
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. The research will focus on identifying and characterizing ultrasonic signatures emitted by aging electronic components, and on developing physics-informed neural networks (PINNs) to model their degradation