870 professor-computer-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions in United States
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Field
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knowledge, abilities, and skills: Excellent communication skills; knowledge of program R, ArcGIS, spatial analysis, common statistical approaches to wildlife data, ability to operate under adverse field
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research efforts. PREFERRED QUALIFICATIONS: A strong background in murine work, high throughput methods, RNA biology, and/or computational biology are highly desirable. Excellent verbal and written
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biological and quantitative techniques including microscopy, flow cytometry, computational/mathematical modeling, and utilizes approaches from synthetic biology and complex biological systems. Highly motivated
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research program that works both within and at the boundaries of data science/econometric methods and the social sciences to discover, create, and disseminate new knowledge. The successful candidate will
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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/Certifications Job Duties: Perform computer simulation, perform experiment design and testing. Writing project reports, and grant proposals. Supervise and collaborate with graduate students in the lab. Publish
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collections. Responsibilities: Carry out bioinformatic analysis of mammalian genome sequence data and generating novel genome assemblies Use computer software for genome assembly, sequence alignment, and
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees, both focused on multimodal synchrotron characterization of defects and interfaces in oxides and 2D...
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motivated candidates for postdoctoral fellow related to chronic kidney disease. Our research program focuses on identifying mechanisms involved in the progression of chronic kidney disease. Specifically, we
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healthcare. Qualifications Required: PhD (or equivalent) in computer science, statistics, biostatistics, electrical/biomedical engineering, or related quantitative field. Strong background in machine learning