Sort by
Refine Your Search
-
We are seeking a highly motivated and creative Postdoctoral Researcher to join the X-ray Science Division (XSD) at Argonne National Laboratory. The successful candidate will develop web-based AI agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware...
-
needs. As a part of this team, you will : Develop, build and test equipment and perform molten salt separations which support the development of a secure fuel supply for MSRs and nuclear fuel cycle
-
performance. The candidate is expected to publish results in refereed journals and make oral presentations at meetings conferences, symposia, and seminars. The candidate is expected to maintain cognizance
-
will be part of a dynamic team working collaboratively with researchers in Q-NEXT (both at Argonne and other academic and industrial member institutions), and is expected to build on and create new
-
expected to engage scientifically with researchers in the HEP groups at both Argonne and UIUC, building overlapping and complementary research efforts. This advertisement is for a three-year postdoctoral
-
instrument proposed under a DOE Major Item of Equipment (MIE) effort. Building on two decades of APS XRS capability (including the LERIX program at 20-ID) and recent commissioning work at Sector 25
-
. Integrate domain knowledge from power systems with modern ML methods to create physics-informed, interpretable, and operationally relevant solutions. Build and evaluate models using realistic utility or test
-
. The division aims to build lab-wide cross-cutting simulation application capabilities integrating with mathematics, computer science, domain science, and advanced computing architectures and facilities
-
make presentations at scientific meetings Communicate effectively with supervisors, peers, and Laboratory management through status updates, technical research reports, project presentations, and other
-
NAMD Deep Learning Development: Experience developing, validating, and deploying deep learning models, especially using Pytorch Multi-Omic Data Representation: Ability to build deep representations