Develop integrative strategies for a diverse set of omics data (metabolomics, transcriptomics, microbiomics etc.), integrating the outcomes to investigate complex disease in a multi-omics framework.
Apply statistical and machine learning and deep learning algorithms to diverse data of different multi omics data sets and quality to identifying associations and causal relationships driving diseases.
Manage and analyse large datasets for analysis using efficient data structures and providing infrastructure for sharing resources.
Drive novel applications and take responsibility over large and diverse projects.
PhD (or near to completion) in health data science, computer science, artificial intelligence, computational biology, bioinformatics, or similar, or PhD in a healthcare area with a substantial omics component in their work. Candidates with excellent ML/AI, computational and quantitative skills are encouraged to apply.
Ability to:
Demonstrate an understanding of both biomedicine and bio
Innovate and develop ideas into grant
Learn and keep abreast of latest technological, methodological and software
Write concise and timely scientific papers and
Plan and prioritise work effectively to meet
Expertise Scripts in R/Python, especially working with libraries and packages useful for bioinformatics such as the Bioconductor package.
Extensive experience working with omics data and large datasets.
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