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
-
Position Requirements • Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field • Ability to model Argonne’s core
-
, 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
-
experiments. Develop reinforcement learning models to improve gate fidelity. Leverage CNM’s state-of-the-art facilities, including the nanofabrication cleanroom and the Quantum Matter and Device Lab’s dilution
-
technical challenges, develop innovative solutions, and implement practical strategies. Skilled communication and interpersonal skills at all levels of the organization. Ability to model Argonne’s core values
-
technical challenges, develop innovative solutions, and implement practical strategies. Skilled communication and interpersonal skills at all levels of the organization. Ability to model Argonne’s core values
-
and datasets • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term
-
mechanistic studies of catalytic systems Strong written and oral communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Familiarity with ligand design
-
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