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Università degli Studi di Roma Tor Vergata - Dipartimento di Biomedicina e Prevenzione | Italy | about 2 months ago
phenotypes. The post-doc will implement machine-learining and deep-learning fusion piplelines to combine high-dimensional imaging features and-omics data, building interpretable ipredictive models. Activities
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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Specific Requirements The ideal candidate has the following qualifications: - interest in human cognition - experience with neural data, especially EEG or MEG - experience with machine learning models
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. PREFERRED QUALIFICATIONS Master’s degree or higher is preferred Proficient knowledge of AI concepts, including machine learning, deep learning, and agentic AI, and how models are developed, trained, and
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
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, thoughtful, and trusted. We envision a model where individuals think beyond their roles, teams are fully engaged, and the organization takes shared ownership of outcomes, challenging convention and
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California State University, San Bernardino | San Bernardino, California | United States | 10 days ago
eager to learn about CSUSB Palm Desert Campus (PDC), including its policies, people, and programs, and be excited to share that information with new students and their families. Role Model Qualities
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, machine learning or neuronal population analyses would be an advantage. Specific Requirements We are looking for a candidate with a strong interest in scientific software development and quantitative
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analysis and exploratory data analysis. Experience applying machine learning methods, including both supervised and unsupervised approaches. Experience evaluating predictive models using appropriate
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assessment of seed yield and quality traits using imaging, machine learning, and edge computing technologies. The position will assist with the development, testing, and deployment of AI models for analyzing