41 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "ISCTE IUL" Postdoctoral positions at Argonne
Sort by
Refine Your Search
-
The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and
-
of funds. Relevant Publications: 1. P. Chen et al ., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1 . 2
-
may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
-
, Quantum Information and Quantum Simulation. The successful candidate will be expected to carry out an independent and collaborative research program in particle theory that strengthens and complements
-
to/from the memory via optical fibers. The candidate will be primarily responsible for: (1) advancing our experimental program to fabricate new hybrid devices in Argonne’s Center for Nanoscale Materials
-
linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
-
artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision Higgs and Standard Model measurements, and searches
-
-completed PhD (within the last 0-5 years) in field of physics, engineering, or a closely related field Demonstrated programming proficiency in C/C++, Python, or another scientific programming language
-
on experiment progress, technique development, and new initiatives to peer reviewers and Q-NEXT program managers Position Requirements Completed Ph.D. within the last 0-5 years (or soon-to-be-completed) in
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran