7 computer-programmer-"FEMTO-ST"-"FEMTO-ST" Fellowship positions at University of North Carolina at Charlotte
Sort by
Refine Your Search
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 5 hours ago
& Computer Engineering Work Location EPIC Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Part-time Hours per week 40 Work Schedule Pay Rate $48,000 - $53,000 Minimum
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 3 months ago
Position Information General Information Position Number STMP18 Working Title Postdoctoral Fellow - Bioinformatics (Temp) Division Academic Affairs Department Coll of Computing&Informatics (Col
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 5 hours ago
documentation, and oral communications and use this information to make judgments about what step(s) will next lead to progress. Departmental Preferred Experience, Skills, Training/Education: Strong computational
-
Position Information General Information Position Number POST40 Working Title Postdoctoral Fellow - Bioinformatics Division Academic Affairs Department Coll of Computing&Informatics (Col) Work Unit
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 2 months ago
Experience, Skills, Training/Education: Preferred Qualifications • Prior primary data collection experience, particularly in the area of physical activity • Strong computational and analytical skills
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 2 months ago
expertise: Strong computational skills are required. Background microbial ecology, metagenomics, molecular genetics, evolution are not required but are highly desirable. Duties and Responsibilities A
-
University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 2 months ago
Experience, Skills, Training/Education: Preferred Qualifications • Prior primary data collection experience, particularly in the area of physical activity • Strong computational and analytical skills