20 machine-learning-"https:"-"https:"-"https:" uni jobs at Lawrence Berkeley National Laboratory
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wide range of numerical and machine learning (ML) computer algorithms as applied to reservoir engineering and geophysical imaging. This includes the simulation of thermal-hydro-mechanical-chemical (THMC
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Mandatory 3 Years of Postdoctoral research experience or equivalent research experience. Past Experience in either Machine learning accelerators or SRAM array design or basic blocks of processor at transistor
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recognized four year apprenticeship program in plant maintenance or completion of an accredited two-year program with two years of work experience; or an equivalent combination of documentable military or
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instrumentation and Software development experience in a multidisciplinary environment. Desired skills/knowledge: Working knowledge of Machine Learning methods applied to scientific data and self-driving laboratory
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experience in Bioinformatics or an equivalent combination of education and experience. Experience with Jupiter Notebooks, including database structure and management. Experience applying machine learning
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complex electronic systems. Able to work independently and exercise sound technical judgment. Familiar with equipment design principles and techniques. Proficient in standard computer applications
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teams by transforming conceptual ideas into complete 3D Computer-Aided Design (CAD) models and detailed 2D drawings. These models and drawings are critical to the manufacturing, fabrication, and
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for software bugs. Provide effective line management to a group of approximately 10 Computer Systems Engineers by hiring excellent staff and working closely with SSG staff members. Ensure staff are meeting goals
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team of quantum algorithm developers, physicists, mathematicians and computer scientists that will design and deliver novel algorithms, error mitigation and compiling techniques for DOE relevant science
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) to define and execute mechanical design solutions. Effectively communicates design intent using GD&T to internal and external fabrication teams. Demonstrated adaptability in learning and applying new tools