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Field
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extend and develop. Job Requirements REQUIRED: Ph.D., in applied mathematics, atmospheric or oceanic sciences, computer science, engineering, physics, statistics, or a related field by the date of hire
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collaborative research program at the intersection of lipid biology, cell death, and evolutionary genomics. The project, primarily led by the Atilla Laboratory (Department of Chemistry ), investigates how lipid
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Employee wellbeing program Financial counseling services Employee Assistance Program with eight sessions of counseling at no cost How To Apply Applications must be submitted online. To be considered
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, citizenship and global outreach. Connections working at University of Idaho More Jobs from This Employer https://main.hercjobs.org/jobs/21656956/postdoctoral-research-associate-statistical-and-computational
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evaluation.This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology/chemistry, machine-learning for biological or chemical data, and
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research journals. Minimum Qualifications Education Required: MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Ph.D. in immunology, genetic
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mentorship of junior lab members (Research Assistants, Graduate Assistants, Student Research Assistants, etc.) Qualifications: Ph.D. in Psychology, Communication, Neuroscience, Rehabilitation Science, Computer Science
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in materials physics and defect properties Required Education: PhD in Materials Science and Engineering Required Experience: Experience with VASP and high-performance computing; A background in
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, materials, virology, computational biology, science communication, community engagement, and ethics. Candidates should demonstrate all relevant qualifications (see required and preferred qualifications below
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Systems Department, in the School of Computer Science, at Carnegie Mellon University is looking to hire two Post-Doctoral Associate who are interested in applying computational social science approaches