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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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of a team member who can optimally get along with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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, optimize, and analyze high throughput functional assays and pooled library screens Help with the validation of candidate variants and genes in mouse models Analyze data using relevant software and present
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of a team member who can optimally get along with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through
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at 479.575.5351. Department: Biomedical Engineering Hourly and GAs Department's Website: https://engineering.uark.edu/ Summary of Job Duties: The Postdoctoral Fellow will lead the development and optimization
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Knowledge, Skills, and Abilities: PhD in Chemistry, Physics, Biophysics, Biology, Biochemistry or Structural Biology. Proven ability to optimize peptide, protein or nucleic acid crystallization systems. Basic
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characterization of electrode materials Design, operate and optimize electrochemical reactors and separation systems, analyze and interpret data using electrochemical and materials characterization techniques (e.g
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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is 7/1/24. Qualifications Completed PhD or a foreign equivalent. The current project seeks to revolutionize the entire process from data to prediction with a paramount focus on reproducibility and