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) Solid expertise in qualitative social research (e.g., conducting qualitative interviews, analysing qualitative data); basic knowledge of quantitative data collection and statistical analysis is an asset
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-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply
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corresponding scientific project management is desirable Confident in independent bioinformatic and statistical analysis of high-throughput sequencing data Experience in working with biofilms is desirable
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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email will not be considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity
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, Genetics, Cell Biology, Biophysics or a related field - Competency in computational (R or Python) and statistical analysis - Competency in experimental design and standard molecular biology, imaging
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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Training: A Ph.D. in biomedical science, engineering, bioinformatics, or related areas is required. Backgrounds in cell and molecular biology, cell culture, imaging, statistics are preferred but not required