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Field
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will include significant opportunities for field research and community engagement in archaeology/ historical archeology. The successful candidate will teach introductory and advanced classes in
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to students and to meet individually with students throughout the semester. Part-Time faculty may teach in the fall, spring, and/or summer semesters. Classes at Georgia Gwinnett College are offered morning
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University of Virginia - Center for Public Health Genomics | Charlottesville, Virginia | United States | 6 days ago
, diagnosis, and/or prognosis. Computational biologist: Candidates should have expertise in computational biology, statistical modeling, machine learning, and artificial intelligence method development with a
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of our students. We are the newest college in Washington State's community and technical college system, and take great pride in our learning environment focused on diversity, equity and inclusion, as
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and apply advanced computational techniques related to statistical genetics, algorithm design, machine learning, artificial intelligence, and knowledge graph construction, data visualization, and/or
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collaborative learning. The ability to work collaboratively with others in a professional setting. Physical Requirements: The Position: typically works in an office environment and uses a computer, telephone and
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summary, go to: Part Time Faculty Benefits Position Summary Information Position Summary Purpose, Scope & Dimension of Job: Faculty facilitate student learning and initiate and participate in efforts
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affiliated with numerous degree-granting programs in the biological and physical sciences. The appointee will teach at the undergraduate and/or graduate level. Compensation (including a generous package of
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needs during the Academic Year. Your application may be considered for substitute assignments as well as full term class assignments. Learn more about our program here https://www.pcc.edu/programs
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. Computational genetics/genomics, including skills in clinical informatics, genomic data science, multi-omic analyses, biostatistical methods and analysis, machine learning, artificial intelligence, reproducible