48 development-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Argonne
Sort by
Refine Your Search
-
The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on the development of single electron on solid neon qubits. The project aims to
-
, enabling multimodal in-situ investigation in areas of physics, chemistry, life and material sciences. We are seeking to fill a Postdoctoral Appointee position to support instrumentation development
-
development of next-generation AI approaches. The successful candidate will perform quantum mechanical calculations to investigate catalytic active sites and reaction mechanisms in heterogeneous catalytic
-
. Demonstrated experience in quantum sensing, quantum information science, superconducting circuit, or magnonics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS or similar
-
experiments, antiferromagnetic spintronics, or cavity spintronics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS). Demonstrated ability to work independently and
-
performance studies, detector operations, and/or upgrade activities Strong skills in scientific programming, software development, and data analysis Ability to work effectively in a collaborative
-
, PyTorch, and the Python scientific stack (e.g., numpy, pandas, scikit-learn). Passion for front-end development and web-based applications, back-end services and API design (e.g., FastAPI, Flask), and
-
characterizing new materials and membranes for critical minerals separations. The ideal candidate will have expertise in membrane development and electrochemical processes. This position will be
-
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 will
-
, discussion of technical results, and in the development of technical reports and presentations is required. Knowledge of the use of computers to design and control experiments and to analyze and interpret