Sort by
Refine Your Search
-
knowledge in bioinformatics and data analysis (e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of clinical genomics, single cell RNA-sequencing and transcriptomics
-
research team to conduct data analysis for different types of data, including genomic/metagenomic sequencing data, ecological surveillance data, as well as development of analysis pipeline. Working off
-
, such as cell culture, flow cytometry, cell sorting, immunohistochemistry staining and data analysis for single cell sequencing. Candidates must exhibit a strong command of written and spoken English, and
-
sequencing and bioinformatics, iPSC derived cells, tissue organoids and/or tissue slices, analytical techniques e.g. LC-MS, liquid scintillation, HPLC, MS, NMR. Administrative and Collaborative Skills
-
handling and culturing, surgical implantation of brain cancer, cryo-electron microscopy, transcriptome, proteome, single cell sequencing and bioinformatics, iPSC derived cells, tissue organoids and/or tissue
-
within a team environment is crucial. The appointee will contribute to research projects aligned with SCoSEIA’s core themes: Understanding the Nature of Income and Wealth Inequality and Wealth Creation
-
. The ability to work independently and collaboratively within a team environment is crucial. The appointee will contribute to research projects aligned with SCoSEIA’s core themes: Understanding the Nature
-
. Documentary proof of qualification may be required an outstanding record of research performance, with a research area that aligns with the focus of FOSS (HKU) and ISR (Michigan) good interpersonal
-
initiatives develop, coordinate, and manage clinical trials in alignment with regulatory standards draft and submit grant proposals to secure research funding apply bioinformatics, biostatistics, and
-
. Preference will be given to those with expertise in innovative methods of advanced statistics and/or learning analytics, such as multiple linear regression, mediation analysis, mixed-effect models, process