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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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, development of data (pre-)processing pipelines, and machine learning model training to identify relevant biological states of the liver (e.g., healthy, recovering, not healthy). The (soft) sensor development
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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facilitate data sharing among actors involved in a new circular flow of flat glass. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented PHD-studenT iN NeuroAI of Developmental vision (m/f/x) Job description A PHD-studenT iN
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computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as