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Field
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or Cloud computing and machine learning techniques? You stand out from your peers because of strong commitment and independent work? You are a team player and communicative (excellent oral and written
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computer vision models for forest-based 3D point cloud data. In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek
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electromagnetic device performance analysis>>>Embedded SystemsResearch focuses on:•Robotics, computer vision, and machine learning/deep learning•Wearable and implantable sensors, biosensors, and tele
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principles, lab measurement, computer vision and ArcGIS, potential fieldwork and UAV flying training. Person specification Experience and/or enthusiastic interest in one or more of the following areas
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methods in forestry generate vast quantities of data and demand more accurate information. Machine learning allows for the systematization and processing of this data into new forms of information
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paraganglioma driven by cell plasticity using spatial transcriptomics and machine learning.” High-risk neuroblastoma (NB) and malignant paraganglioma (PPGL) are neural crest–derived tumors with pronounced
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detailed data about forest ecosystems. To convert the captured data into meaningful information about the forest environment we seek a PhD candidate who wishes to advance state-of-the-art computer vision
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AI, human-AI collaboration systems, computer vision (CV) models, and natural language processing (NLP) models. Candidates with expertise in any of these areas are encouraged to apply, as the position
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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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Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic Disentanglement of the Exceptional Biological Learning Machine, which is headed by Professor Jan