282 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions at Monash University in Australia
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
compliance with privacy, confidentiality, and regulatory requirements, including student visa processes. It involves the accurate input, analysis, and management of data and records, providing sound and timely
-
of the ARC Laureate Fellowship, providing hands-on support for data-intensive research activities. It will contribute to the curation and processing of UK Biobank data and assist in developing an integrated
-
, maintain laboratory equipment and supplies, analyse data, update operating procedures, and assist with research administration. You will also help train staff in selected laboratory techniques and ensure a
-
, characterization and evaluation of novel PfM1 and M17 aminopeptidase inhibitors. This would include compound design, data management and analysis and sample preparation as well as a range of drug discovery-related
-
registered higher education provider under the TEQSA Act 2011. We acknowledge and pay respects to the Elders and Traditional Owners of the land on which our five Australian campuses stand. Information
-
measurements in particle physics. Many of my projects are informed directly by current measurements, e.g. addressing new or unexpected features seen in the data. Others focus on improving the formal accuracy
-
weighted sum of the risks from tens to millions of independent disease-associated SNPs from across the genome. The conventional, or gold-standard, approach to analysis of GWAS data is to fit a regression
-
an electrical and computer systems engineering degree in the Faculty of Engineering. Total scholarship value $20,000 Number offered One at any time See details Farrell Raharjo Clive Weeks Community Leadership
-
increasingly rely on digital systems to issue, store, and verify qualifications, new risks arise—ranging from data breaches and identity fraud to profiling and surveillance through credential verification logs
-
, and their decisions can be confusing due to brittleness, there is a critical need to understand their behaviour, analyse the (potential) failures of the models (or the data used to train them), debug