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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
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ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a multidisciplinary
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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simulations of PDEs, deep learning, neural networks. Our research interest: Our focus is on theoretical and computational biological physics, ranging from the study of molecules to cells. We strive to leverage
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during infection using machine learning Detailed information on and specific requirements for each project is given below. The IceLab Multidisciplinary Postdoctoral Program funded by Kempestiftelserna
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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About the Opportunity Job Summary The Data-Driven Renewables Research (D2R2) group led by Dr. Peter Schindler is accepting applications for a postdoctoral research associate in the field
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. Preferred: • Strong programming skills in languages such as R/Python • Research background in biostatistics/statistical genetics/population genetics/deep learning and LLM • Experience in any of the following
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Posting Details Posting Details Logo Institution South Dakota Mines Working Title Postdoctoral Researcher Posting Number NFE02794P Department SDSMT-Physics 1 Physical Location of Position (City
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methods, stochastic control processes, dynamic programming, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong programming skills