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Field
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models, with an emphasis on techniques such as knowledge distillation. The candidate will engage in research involving time-series analysis, including modeling, forecasting, and anomaly detection
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Your key responsibilities will be to: develop fundamental theories and enabling technologies for intelligent wireless communication systems design, model and evaluate integrated communication, sensing
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centralized. The successful candidates will work at the intersection of federated learning, foundation models, multimodal biomedical AI, privacy-preserving machine learning, continuous learning, and agentic AI
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background in Mathematics/Applied Mathematics, particularly in research areas such as Applied Analysis/Computational Mathematics/Mathematical Modeling/Probability and Statistics, along with excellent
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About the Opportunity AI-Driven Ultrasound and Intelligent Sensing: We are seeking a postdoctoral researcher to work on quantitative ultrasound methods, focusing on the application of model-based
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a strong background in Biochemistry, Mathematics, and/or Mechanics (experimental and computational methods (use of OpenFOAM and/or COMSOL)) are welcome to apply. Experience in blood and animal
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method development and large-scale research facilities. Essential Duties and Responsibilities Develop workflows to improve models and maps to optimize likelihood for ligand placement Develop AI/ML methods
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research projects Experience in working in an international team Solid understanding of data-driven modelling and related mathematical and statistical methods Excellent communication skills Proactivity
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-driven atomistic modeling and AI-accelerated cheminformatics to join the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), hosted by the Department of Chemistry and Materials Science (CMAT
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partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across the two teams. The position offers a strong publication trajectory at leading HCI venues