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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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, and proficiency in use of AI concepts, including machine learning, deep learning, and agentic AI, and how models are developed, trained, and validated ● Demonstrated familiarity with AI tools and their
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UiO/Anders Lien 16th October 2026 Languages English English English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat
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LevelMaster Degree or equivalent Skills/Qualifications Solid background in Machine Learning and Deep Learning. Experience or interest in agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, or similar
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 12 hours ago
Do you want to help transform human health through machine learning and life science approaches? Join AITHYRA in Vienna for a fully funded PhD at the intersection of machine learning, experimental
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ability to deliver solutions from scoping and data analysis through deployment and documentation. Applied Machine Learning: Possess deep, practical knowledge of machine learning fundamentals, with proven
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environment. 4) Development of machine learning and deep learning models for forecasting reduced visibility, low cloud ceilings, and adverse weather conditions impacting air operations. 5) Implementation
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways
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environments; (2) identify which patterns of student-AI interactions influence the adoption of deep or surface approaches to learning; (3) create, implement and evaluate guidelines and knowledge base