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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 4 days ago
, improving lives. The Horvath Lab at the Institute of AI for Health (AIH) aims to build large deep learning models for digital pathology to resolve single cell heterogeneity and identify subtle cellular
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University Medical Center of the Johannes Gutenberg University Mainz | Mainz, Rheinland Pfalz | Germany | 8 days ago
The PhD student will: Develop and evaluate statistical and machine learning models for survival analysis Perform methodological comparisons and validation studies Analyze high-dimensional molecular and
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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of models like CNN, RNN, Transformers with some work in classical machine learning with XGBDTs is expected. Relevant work can lead to co-author publications and contributions to grant proposals. Tentative
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geometries. However, AM-generated surfaces exhibit significant and highly irregular roughness, a key factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined
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Developer for the Crop and Science Department at Oregon State University (OSU). We’re looking for a motivated student to develop computer vision models that detect and classify important agricultural elements
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Memorial Sloan-Kettering Cancer Center | New York City, New York | United States | about 12 hours ago
the development of realtime motion adaptation during treatment on the MR-linac and conventional linac platforms, the development and clinical use of predictive models using machine learning/AI for treatment
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. They will learn to design interpretable, legally robust AI systems, including attention-based deep learning models and reinforcement learning approaches that adapt lineup presentation in real time based
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP