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: Analyse and publish data from a large clinical SLP data-base (year 1) conduct a Delphi process to establish what data should be collected to create a national laryngeal disorders database in ENT/SLP.(year 2
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effects in patients with psychiatric disorders. The primary focus will be on the development of polygenic scores in large datasets, including in the UK Biobank (N=500,000), US All of Us Program data (N~1
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computational skills and experience in R, Python, Jupyter, Notebook, and genetic/genomic tools (e.g., PLINK2, GCTA, MR, FUMA). Experience with big data analytics within Linux and cloud computing environments, and
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consideration to candidates currently completing a PhD in Economics or a related field (such as Statistics or Applied Data Science). Demonstrated research experience, including academic and/or commissioned
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the design, analysis and interpretation of data from longitudinal cohort studies. Analyse large scale administrative data. Lead and contribute to preparation of peer-review publications and reports Be involved
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Information Systems Salary: Level A $83,468- $113,262 with a PhD starting salary of (A.6) of $105,518 p.a. plus 17% super. Conduct research into digital storytelling with older adults, empowering them to create
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Cell (2016), Cancer Discovery (2024), and Nature Cancer (2021). Importantly, several of our discoveries have translated into large-scale clinical trials. Essential requirements PhD in cancer biology
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criterion, we will consider candidates currently completing a PhD in Economics or a related field (such as Statistics or Applied Data Science) and who have a strong research record and demonstrated research
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genome data Develop a pioneering genomic clone risk framework, shaping future surveillance strategies and vaccine development Key Selection Criteria: PhD in bacterial genetics, genomics, or related fields
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 21 days ago
experience in any of the following are encouraged to apply : stellar spectroscopy and stellar abundances, stellar structure and stellar evolution, chemical evolution modelling, large survey data, statistics