27 programming-"the"-"DAAD"-"EURAXESS"-"IMPRS-ML"-"O.P"-"U" positions at Lawrence Berkeley National Laboratory
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Mathematics Computational Research Division (AMCR) has an immediate opening in the Quantum Information Science and Technology Group (QuIST) for a Quantum Experimentalist Postdoctoral Fellow under the programs
-
electronics and hardware/software integration. Experience with Python-based programming tools for data analysis, automation, and instrument control. Hands-on experience operating and maintaining cryogenic
-
electronics and HPC is to make more efficient use of transistors through architecture specialization, application-specific acceleration, and compilers/programming-models that better control data movement than
-
, and critical alarm notifications essential to scientific programs. As part of LBNL's Facilities Engineering Team, the Control Systems Engineer (CSE) will design, manage, and maintain these systems
-
) project as well as future superconducting based Quantum Information Science and Technology efforts. The AQT program is focused on constructing, enhancing, operating, and maintaining an open, fully
-
Python programming for scientific instrumentation. Ability and willingness to learn new scientific and technical concepts. Scientific instrumentation and Software development experience, preferably in a
-
career - check out our Tuition Assistance Program A culture where you'll belong - we are invested in our teams! In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every
-
projects. Plan, organize, track, and execute projects on behalf of our Science IT customers as part of a flexible team organization. Foster a cross-domain community and knowledge-sharing among science teams
-
, to analyze performance, improve portability and reliability, and bring new workflow capabilities to thousands of users across DOE Office of Science programs. What You Will Do: Contribute to one or more NESAP
-
engage in AI/ML-based inverse modeling for the analysis of well test and fluid-flow experimental data, the development and deployment of AI/ML models into software tools and programs, and performance