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and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami) at the Department of Computer Science, aligning with
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boosting, and related machine-learning approaches Evaluation of model generalizability using train/test splits, leave-one-cohort-out validation, and leave-one-platform-out validation Assessment of predictive
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pathophysiological mechanisms for acute organ injury research under POI-KB. · Authorship of high-impact first-author or co-author manuscripts in leading informatics and machine learning journals and conferences
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and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami) at the Department of Computer Science, aligning with
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5, Franka Emika
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has a fixed-term opportunity for a Postdoctoral Fellow / Senior Research Fellow to contribute to world-leading research in continual learning, computer vision, multimodal foundation models, and
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to regulatory agencies, investors, pharma companies etc. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Develop models
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs