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Field
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several projects in parallel Ability to work collaboratively in a team as well as independently on a wide variety of research projects Excellent communication skills Detail-oriented, focused, and highly
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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University of California, Los Angeles | Los Angeles, California | United States | about 19 hours ago
knowledge of laboratory genetics and genomics, including target capture, amplification, and massively parallel sequencing. • Familiarity with widely used genomic tools such as IGV and UCSC/COSMIC genome
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therapies. The role emphasizes continuity of care and coordination across infusion, exam, and supportive services. The APP conducts independent patient assessments and also works in parallel with attending
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eigenvalue problems Experience of MPI, OpenMP, and other parallel programming models Understanding of quantum many-body problem and tensor eigenvalue problem Excellent oral and written communication skills
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the development, support, parallelization, optimization, and benchmarking of scientific applications and code using tools like Fortran, C/C++, MPI, OpenMP • Experience with and a thorough knowledge of queuing
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current practice). Demonstrated expertise in AI/ML. Proven track record in application performance optimization. Advanced experience with parallel programming models (e.g., OpenMP, MPI, CUDA). Extensive
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field from an accredited institution. Demonstrated skills in creative problem solving and troubleshooting Experience with parallel computing and multi-core \ multi-threaded programming libraries Knowledge
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such as RNA FISH probe generation followed by imaging at the Imaging core, 3) RNA secondary structure analysis with methods such as FISH 4) RNA functional genomics with methods such as massively parallel
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, massively parallel genomic/proteomic/clinical]. Data management and analysis solutions that aid in the storage, investigation, and dissemination of large data sets. Independent research projects, including