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engineering practices for machine learning Tabular machine learning Large language models on structured and semi-structured data Research Associate Role: Under the direction of their supervisor, the candidate
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FieldComputer science » OtherEducation LevelPhD or equivalent Skills/Qualifications CANDIDATE ’S PROFILE The candidate should possess a PhD in machine learning or computer vision and have a strong publication
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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approaches are gaining importance for autonomous vehicles. However, the training and certification of autonomous systems with machine learning components is a huge challenge, since the learned behavior is
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Python, including use of data analysis libraries such as pandas and scikit-learn Experience with Large Language Models (LLMs): using APIs (e.g., OpenAI, HuggingFace), or local models (e.g., Ollama
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economy. Key Responsibilities Acquire, process, manage, and integrate field and satellite data (Sentinel-2, Landsat/HLS). Develop, calibrate, and validate predictive models of vegetation fuel moisture
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machine learning models (e.g., VAEs, GANs, transformer-based models) to large-scale biomedical and biological data, including developing and optimizing models to predict disease progression and create
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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in one of the following areas (or related fields): * Machine learning / deep learning * Quantum computing / quantum
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data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other international initiatives. To be considered, you must
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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high