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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2
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transitions in and out of campus housing, accurate data reporting, and collaborative partnerships across departments. As part of our integrated residential education model, you’ll work closely with professional
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significant challenges for the treatment and supply of safe and high-quality drinking water. The project aims to develop a multiscale predictive analytics framework that integrates long-term algal speciation
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University Work duties: This postdoctoral position is part of the AFLOW consortium supported by the Swedish Energy Agency and focuses on materials modelling of chemical stability in aqueous organic redox flow
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, predictive modeling, and decision support. This role combines deep analytical expertise with business acumen to transform complex data into actionable insights that support strategic planning and financial
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-scale genomic and phenotypic datasets (e.g., PheWAS, statistical genetics, prediction models) Analyze high-dimensional data from biobanks and clinical information systems Contribute to teaching activities
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. Oversees the delivery and operating model for UFA’s data management and reporting function–including roadmaps, Jira/ServiceNow workflows, release/change management–ensuring predictable, transparent, and
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. The successful candidate should apply state-of-the-art methods in either aquatic ecology and biodiversity research (e.g., environmental omics, eDNA, etc.) or hydrology (e.g. integrated modeling and/or AI-based
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types will change under different climate change scenarios based climate projections. This framework will be ultimately included in a flood prediction model, which will be developed within the VIDI
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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational