25 combinatorial-optimization Postdoctoral positions at Oak Ridge National Laboratory in Usa
-
through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
-
Model, working closely with the experimental team to understand this device’s PMI physics and optimize performance of the device in its upcoming campaigns. The position resides in the Power Exhaust and
-
photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
-
support the neutronics and thermal-hydraulics analysis. Major Duties/Responsibilities: Design, develop, optimize and analyze reactor models using world-class modeling and simulation codes (SCALE, VERA
-
, optimize, and test advanced materials that will accelerate the deployment of higher performance nuclear energy systems. As part of our research team, you will assess the viability of accelerated irradiation
-
with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate
-
supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and
-
the development and optimization of products for a variety of industries from automotive to aerospace made from new bio- and waste-derived plastic resins and fillers. The ideal candidate for this role would be
-
for radioactive s-, p-, and f-block metal ions. Independently execute and troubleshoot complex, multi-step organic syntheses on the multi-gram scale, including reaction optimization, scale-up, purification, and
-
. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral