Sort by
Refine Your Search
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
-
phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in reactive systems Use modeling tools such as computational fluid dynamics
-
The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
-
/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
-
apply funding from federal agencies (e.g., the Department of Energy and National Science Foundation). A successful candidate should have a solid background in power system engineering, optimization
-
Infrastructure Sciences Division. Machine learning (ML), specifically deep learning (DL), has been demonstrated to successfully predict the weather for 1-14 days with skill on par with numerical weather prediction
-
, the postdoc will translate demonstrated prototype performance into a complete, buildable engineering specifications package for a scaled multi-element analyzer spectrometer and associated microscope/imaging
-
Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Chemistry, Chemical Engineering, Mechanical Engineering, Materials Science, Electrochemistry, or a related
-
The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in experimental condensed matter physics. Although exceptional candidates in
-
Recent or soon-to-be completed (typically within the last 0-5 years ) Ph.D. in Computer Science, Electrical Engineering, or a related field. Demonstrated research expertise in AI and machine learning, with