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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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integrating advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques with process-based crop models, this research will empower farmers to optimize conservation practices, increase
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Salmonella detection methodologies. Learning Objectives: The participant will learn about stakeholder-focused research, data science, scientific communication, food safety applications, real-world data, and
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, or a related discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage
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About the University As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research
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will contribute to the project’s research agenda by helping to identify collect, acquire, clean, and manage datasets on ownership of U.S. and European public and private firms, conducting sophisticated
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | about 9 hours ago
proteins are recognized by antibodies at an atomic level, and how that recognition can be exploited to design effective vaccines. You will learn to design and execute experiments to determine the structures
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background in earthquake monitoring. The successful candidate will lead and contribute to developing a machine-learning powered earthquake monitoring and early warning system. The role involves both
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Australia’s future change-makers and create a better tomorrow. Work that matters Contribute to cutting-edge research in AI-enabled satellite autonomy, developing reinforcement learning solutions for real-time