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Field
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
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from different fields: AI (machine learning, big database, etc) Semiconductors
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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, etc.) o Energetic frustration or protein energy landscape analysis o Machine learning in protein science o +2 years of experience after PhD Knowledge of evolutionary biology concepts (phylogenetics
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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understanding and generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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. Teaching skills. Additional assessment criteria: A strong ability to develop and conduct high-quality research independently. Experience using deep learning methods and computer vision with biological data
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in core methods of machine learning/artificial intelligence. ● Experience with data warehousing and building large, curated datasets with protected health information, suitable for training large