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Field
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, Division of Applied Mathematical Science (Team Director; Eiryo Kawakami) (5) Medical Science Deep Learning Team , Division of Applied Mathematical Science (Team Director; Jun Seita) (6) Prediction
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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foundation and programming skills in languages such as Python, Java, Julia, MATLAB, R, and/or C++. Expertise in one or more of the following: machine learning, deep learning, HPC, Docker/Singularity
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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functional data analysis, tensor regression, high-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated
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with electronic health record (EHR) and/or clinical data. Proficiency in Python, with strong coding and debugging skills. Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow
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, Coastal Marine Science, Computer Science, Electrical Engineering, or a closely related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and
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university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity
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of biosignals features and processing techniques. Experience in designing Spiking Neural Networks (SNNs) or deep learning algorithms Preferably, experience with FPGA development of SNNs ASIC design experience is
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skills. Excellent programming skills in Python and Julia with experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Experience building complex software systems, preferably with industry