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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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in one or more of the following areas: computational biology/bioinformatics, biomedical informatics, deep learning/machine learning, data mining, biostatistics, or a closely related area. Proficiency
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Professor Hing Leung and the wider multi-disciplinary research team. We are looking for candidates with experience/strong interests in learning some of the following: deep learning, medical imaging, and
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ATAC-seq, single-cell RNA-seq, spatial gene expression, and whole-genome sequencing (with long reads) data. The candidate will get the opportunity to explore new analysis methods using deep learning
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California State University, Northridge | Northridge, California | United States | about 2 months ago
Apply now Job no:533435 Work type:Auxiliary Location:Northridge Categories:Full Time Duties and Responsibilities: Join an inspiring convergence research team that champions deep integration across
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States of America [map ] Appl Deadline: (posted 2025/01/10, listed until 2025/07/10) Position Description: Position Description Multiphysics, Machine Learning, and Uncertainty Quantification Postdoctoral Positions Los
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theory and applications, instrumentation and signal processing and cloud microphysics and dynamics. Strong programming abilities (like Python), statistical knowledge, machine learning expertise, and data
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, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing ● Emerging AI/ML models and hardware
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theory and applications, instrumentation and signal processing and cloud microphysics and dynamics. Strong programming abilities (like Python), statistical knowledge, machine learning expertise, and data
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calculations Materials modeling/electronic structure calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed