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and the Biogeochemical Modelling Research Group in the department of Physical Oceanography at IOW, you will curate a time series of in situ, remotely sensed and modelled inherent and apparent optical
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complex algorithms and predictive models and determine analytical approaches and modeling techniques to evaluate potential future outcomes. Establish analytical rigor and statistical methods to analyze
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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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Work type: Full-time School: School of Computer Science Subject Area: Cyberspace Security, Artificial Intelligence, Big Data, Computer Networks, Multimedia, etc. Introduce: Chongqing University’s
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complex terrain regions. CMAS does this by innovating on the fronts of meteorological data acquisition, analysis, and interpretation (https://www.bnl.gov/cmas/). The CMAS work portfolio is conducted within
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» Algorithms Researcher Profile First Stage Researcher (R1) Country France Application Deadline 26 Mar 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1
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experience of multi-variate time-series analysis, to work on a NERC-funded project “Multigenerational Trophic Responses to Coupled Short- and Long-term Environmental Change” for up to 6 months. Our project
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-modal data processing for real-world robotic applications. Strong background in deep learning, supervised and unsupervised learning, time-series analysis, information visualisation, with experience in
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practitioners. The Fellow will also teach one course per year. Throughout the fellowship period, the Fellow will work alongside other Post-Doctoral fellows at GRI and participate in a professional development
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14 Feb 2025 Job Information Organisation/Company CNRS Department Centre de recherche en Paléontologie, Paris Research Field Geosciences Astronomy Environmental science Researcher Profile First Stage