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Field
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actively contribute to the WeForming and EnerTEF projects. WeForming and EnerTEF propose developing automatized and intelligent solution for operating active distributed grids with multiple active asset6s
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occurring at multiple scales in subsurface energy storage and recovery systems. An interdisciplinary team, including experts from UTEP, Florida State University, the University of Utah, Sandia National Lab
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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research fellow position. The successful candidate for this position will work with Drs. Kathryn Colborn and Elizabeth Juarez-Colunga. The selected candidate will benefit from and contribute to multiple
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and administrative activities, coordinating multiple aspects of work to meet deadlines. 2) Undertake comprehensive and systematic literature reviews to develop projects. 3) Adapt existing and develop
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for the eastern US. Multiple peer-reviewed publications are expected to result from this work, to be developed in tandem with key project personnel and collaborators. Travel funding is available to present research
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other characterization methods, as well as across multiple CNMS groups and divisions at ORNL. Major Duties/Responsibilities: Conduct materials research using combined photonics/scanning probe microscopy
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control) due to multiple interacting disturbances such as wildfires, drought, and insect outbreaks. The researcher will apply and adapt a spatially explicit multi-hazard risk assessment framework developed
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 3 months ago
of multiple timescales. Collectively induced stochastic resonance phenomena on molecular ensembles in optical cavities. Cavity-induced off-equilibrium consequences on chemical reaction rates Develop (ab-initio