Sort by
Refine Your Search
-
methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
-
agencies and other national laboratories. The candidate will develop power systems and electricity market modeling, and analytics tools that support energy, economic, and financial analyses of power grid
-
, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
-
The Center for Nanoscale Materials (CNM) at Argonne National Laboratory invites applications for a postdoctoral researcher position in the field of hybrid quantum computing. This exciting project
-
other sources to train and validate AI models. Develop computational workflows incorporating LLMs, Monte Carlo Tree Search (MCTS), phylogenetic inference, uncertainty quantification, and epidemiological
-
models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
-
to the development of new research directions aligned with program goals. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Chemical Engineering, Materials
-
advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
-
phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use modeling tools such as computational fluid
-
techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good