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of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no ), a center for
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 2 months ago
not strictly required. Skills or interest in MRI processing (especially diffusion MRI), biophysical neural modeling, and machine learning are welcome. What we offer The Institute offers a world-leading
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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synthesis over all relevant length scales (e.g. cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) • High resolution analysis, monitoring of chemistry
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. This simple unit is limiting the learning capabilities of recurrent neural network models in tasks characterized by multi-timescale and long-range temporal dependencies. To implement multi-scale adaptation, in
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Are you passionate about hardware security, side-channel analysis and machine learning? Do you want to contribute to research within an international environment? If the answer is yes, please
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to protect AI models against data leakage during inter-departmental information sharing. With the National Police heavily relying on sensitive data exchanges, this research will develop secure machine learning
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modifications using high-resolution mass spectrometry and AI-based de novo peptide sequencing. Develop and apply machine learning models to predict protease activity and substrate specificity, integrating protein
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into **influence functions**, theoretical tools designed to quantify the impact of a sample on a machine learning model. These functions, defined through the derivative of model parameters or the loss function with