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modeling. Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general
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photo-bases. The work will focus on modeling of adiabatic and nonadiabatic photochemical processes to capture excited states dynamics using an array of ab initio molecular dynamics methods for excited
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on the development and application of machine learning algorithms in areas such as surrogate modeling for physical systems, data assimilation, and scientific data reduction. The position comes with a travel allowance
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Postdoctoral Researcher - Microstructural Modeling and Characterization of High-temperature Ceramics
Requisition Id 14543 Overview: We are seeking a Postdoc who will focus on microstructural characterizations of nuclear ceramics and mechanistic modeling of the material degradation behavior under
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CCSI initiative called Science and Technology for Applied Regional Solutions (CCSI STARS). Major Job Duties/Responsibilities: The researcher will synthesize and analyze observational data and modeling
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. Construct machine-learning models for feature-based molecular property prediction and drive the inverse design of ligands with engineered properties. Develop machine-learned interatomic potentials trained
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techniques (such as, large language models) in the neutron powder diffraction data life cycle. This work will be conducted collaboratively with other scientists within the Neutron Scattering Division and
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. You will also have the opportunity to collaborate with in-house building scientists on cutting-edge research in areas such as building envelopes, HVAC systems, and building energy modeling. Major Duties
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, to identify and accelerate technological and policy options. Activities will involve: 1) data collection, processing, and quality assurance; 2) development and simulation of energy system models, data science
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to the performance of high-power accelerators such as the Spallation Neutron Source (SNS). The goal of this work is to demonstrate predictive modeling of beam distributions in a realistic accelerator, and as such