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.) degree in area of research specialty. Required Certification, Licensure/Other Credentials Preferred Qualifications Doctoral (Ph.D.) degree in biostatistics, bioinformatics, or other relevant public health
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
, data analysis, and bioinformatics, and a good track of publication records in related areas to conduct basic and translational cancer research in the Dr. Jeremy Rich’s laboratory for brain tumor studies
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. Applicants should hold a PhD in computational biology, bioinformatics, systems biology, computer science, or a related quantitative discipline, with relevant postdoctoral research experience. Demonstrated
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initiative Preferred Qualifications: Published microscopy (widefield or confocal) techniques Evidence of prior bioinformatics analysis Published HIV-1 research Literature fluency particularly viral RNA biology
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Solid experience in nucleic acid isolation, PCR, RT-qPCR, and gel electrophoresis Solid experience in gene overexpression and/or silencing Proven knowledge in either four of these bioinformatics tools
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cytometry • Bioinformatics (R ) • Analytical reasoning ability, organization skills, team spirit • 0 to 7 years experience after PhD Additional comments Contact: anne.hosmalin@inserm.fr Duration: 12 months
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experience in Green Synthesis and characterization of nanoparticles Working experience in bioinformatics data analysis with different genomic and transcriptomic tools Working experience in insecticide
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: PhD in genetics, genomics, plant biology, bioinformatics, or a related field completed by the start date. Preferred Qualifications: Experience with plant genomics or crop plants Experience using high
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Classification Title: PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field. Classification Minimum Requirements: PhD in Bioinformatics
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areas would be an advantage: Metabolomics/carbon tracing Plant physiology techniques Characterization of transgenic rice plants (Single-cell) transcriptomics approaches Bioinformatics analyses of large