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to conduct applied research (TRL>1) in the domain of quantum computing and/or machine learning; Possibility to file patent applications within the project; Funds to employ 3 other researchers: 1 postdoc and 2
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 21 days ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
abiotic resources. We integrate remotely sensed information with in-situ data, process-based models, and leverage satellite communication, IoT and machine learning technologies in order to provide evidence
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computational models, applying statistical and machine learning methods, and integrating data across modalities to generate novel scientific insights. The Postdoctoral Fellow will lead manuscript preparation
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computational models, applying statistical and machine learning methods, and integrating data across modalities to generate novel scientific insights. The Postdoctoral Fellow will lead manuscript preparation
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biology skills Experience with single-cell RNA-seq analysis Experience with machine learning based methods Have evidence of scientific accomplishment via peer-reviewed publications Understanding of cancer
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supervising doctoral students. Join us in shaping the future! Your role and goals Your primary task as a postdoc is to conduct research into various quantum algorithms and optimization methods, both
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://postdoc.wustl.edu/prospective-postdocs-2/ . Lab website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning
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Cornell University, Electrical and Computer Engineering Position ID: Cornell-ECE-POSTDOC [#31375] Position Title: Position Type: Postdoctoral Position Location: Ithaca, New York 14853