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basic experimental design. Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting. Familiarity with deep learning concepts
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monitoring agricultural emissions across Africa using satellite remote sensing, atmospheric modeling, and deep learning. Research Focus Estimate cropland emissions (NH3, N2O, CO2, CH4) using satellite
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | about 5 hours ago
signal and image processing, machine learning, deep learning, robotics, and 3D design, with proficiency in programming languages such as JavaScript, R, Python, Matlab, or SQL. • Proven research experience
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Macomb Community College Adjunct Faculty demonstrate deep subject matter knowledge and provide effective instruction to students using various modalities including, but not limited to, on campus, online
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employment. Starting date: 09.04.2026 Job description:PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 987 - 2026/WP 1 Work location: Hamburg Application deadline
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teaching and curriculum development in Python programming, machine learning, deep learning, and modern AI applications. The ideal candidate brings strong applied skills and a commitment to hands-on, project
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, machine learning, and deep learning Good written and oral communication skills Experience in leading research projects Proficiency in basics of programming languages such as Python Self-Motivated and takes
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learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in collaboration
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Macomb Community College Adjunct Faculty demonstrate deep subject matter knowledge and provide effective instruction to students using various modalities including, but not limited to, on campus, online