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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 26 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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the world, we work together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-seismic-detection
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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. Disseminate research through high-impact publications and conference presentations. Requirements: PhD (or near completion) in Imaging Science, Computational Biology, Bioinformatics, Machine Learning, Data
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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Appointing a postdoctoral scholar with expertise in causal inference, machine learning, and
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E-mail jakub.ceranka@vub.be Website https://jobs.vub.be/job/Elsene-PhD-in-'medical-image-analysis-and-artificial-in… Requirements Research FieldEngineering » Biomedical engineeringEducation
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with artificial intelligence (machine learning/deep learning) Essential Application/interview Experience with classical image processing techniques (e.g. classification/segmentation/registration
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and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. We regularly publish solid contributions at the best machine learning conferences. STIMA is
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stability analysis and control, machine learning, dimensionality reduction and high-performance computing. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UPR3346-NADMAA-159/Default.aspx
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degree in AI, Computing Science, Mathematics, or Data Science. Strong coding, communication and organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch