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The Danish Center for Hadal Research (HADAL) at the Department of Biology, University of Southern Denmark, invites applicants for 5 Ph.D. positions in deep-sea biogeochemistry and microbial ecology
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industry needs while working on projects at SIT. Key Responsibilities Design and develop a prototype of an Artificial Intelligence (AI) model with deep learning algorithm to detect, distinguish and identify
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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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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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cardiovascular MRI, cardiac diffusion tensor imaging, and machine learning or deep learning methods applied to imaging is highly desirable. You will be a collaborative and motivated researcher, capable of working
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networks for real-time, adaptive diagnosis. b) Uncertainty in Dynamic Environments: Runtime uncertainties require sophisticated risk modeling; we will employ Bayesian deep learning and deep reinforcement
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candidate will show in-depth methodological and applied knowledge in the field of machine learning, especially deep learning, experiences in the area of uncertainty quantification, generative and Bayesian
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to learn robotics or human-centered research methods will also be considered. Experience with programming languages (particularly Python), deep learning frameworks, and robotic simulation platforms (ROS
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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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-level detection capabilities. Their work involves enhancing the existing deep learning models to ensure high detection accuracy and improve navigation within open-field environments. This person will also