34 electronics-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions at Argonne
Sort by
Refine Your Search
-
science, or a closely related field Experience in the development and/or deployment of superconducting devices, or related technologies in quantum devices, low-temperature systems, microelectronics, or
-
ferroelectric and other functional materials into photonic architectures for electro-optic and quantum transduction applications Perform full device processing using cleanroom techniques, including electron-beam
-
expertise in machine learning, computational imaging, computer vision, or signal processing. Proficiency in scientific programming and modern ML frameworks, with the ability to implement and debug research
-
for experiments, or uncertainty quantification Experience with autonomous, self-driving, or robotic laboratory platforms Background in electronic polymers, conjugated polymers, organic semiconductors, soft
-
the electronic, magnetic, and optical properties of 2D materials at ultrafast timescales, which holds promises for developing new energy technologies. The candidate is responsible for conceiving, planning, and
-
demonstrates a professional attitude. Skilled written and verbal communicator, including the ability to present complex information so that it is understandable to a broad audience. Strong computer skills
-
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
-
for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
-
diffraction, electron microscopy (SEM and TEM), spectroscopy (FTIR and Raman), and electrochemical (EIS and battery cycler). Publication record with excellent written and oral communication skills. Ability
-
together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning