7 software-formal-method-phd Fellowship positions at Lawrence Berkeley National Laboratory
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resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software. Collaborate with computational and domain
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, edge resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software. Publish and present results
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, Materials Science, or a related field. Hands-on experience with first-principles or atomistic methods relevant to interfacial systems, including DFT, ab initio MD, enhanced sampling techniques, or tight
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networking technologies, software, algorithms and applications Evaluating or developing new and promising HPC systems and networking technologies Researching methods to control and manage next-generation
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development. Engage in seminars, workshops, and group meetings to broaden scientific perspective and support growth. What is Required: PhD in a technical field such as chemistry, physics, materials science
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of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from brain organoids. This position
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. (or equivalent) in physics or a closely related field. Strong communication skills and the ability to contribute effectively to large-scale software projects. Proven capability to conduct independent research as