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from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen
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, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML (Random Forest, SVM, Fully Connected Neural Networks) will be essential
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colleagues in Computer and Information Sciences, Economics, Engineering, Natural Resources, and other units on campus. The following materials are required: Letter of interest, with clear indication
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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offered a fully funded contract of up to 3 years. About the position The postdoctoral research position will require developing and applying cutting-edge machine learning methods to computer vision and
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of large biological datasets. The successful candidate will design novel machine learning techniques for cancer data science, incorporating approaches such as Neural Cellular Automata, Neural Ordinary
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A postdoctoral position on exascale atomistic simulations, AI/machine learning and data analysis of ferroelectric devices is available immediately at the Center for Nanoscale Materials (CNM
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using language models to induce programs from text data Experience with computational cognitive modeling Experience with neural networks or other machine learning methods Strong initiative and
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develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques
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Electromagnetic simulation We also welcome researchers from different fields: AI (machine learning, big database, etc) Semiconductors As a minimum requirement, you must have a PhD degree in Electrical and