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Field
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fundamental understanding of droplet flow on single and complex fiber networks. Essential to the project is the development of a new understanding of capillary flow, drop impact, and wetting in fibrous networks
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practices in code development and maintenance (e.g. Github/Gitlab, GitHub Actions, etc). Experience with machine learning or network-based approaches is desirable. Familiarity with FAIR data principles and
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inflammatory bowel disease (IBD) which is located on chromosome 5. The associated locus lies within an uncharacterised long non-coding (lnc)RNA and exhibits strong activation-dependent enhancer activity in
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applications would be particularly beneficial, although not essential. In addition, experience in artificial intelligence, cloud computing, sensor networks and/or data visualisation would also be highly
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communication skills. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis. Knowledge of network science and/or complexity sciences
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. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis or simulations of dynamics. Knowledge of network science and/or complexity
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objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms (50%). PhD in computer science, engineering
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disruptions data and network analysis, the candidate should have a strong background in network modelling and coding. The selected candidate will also have excellent leadership ability/potential and strong
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. The fellowship period is 3 years. The project will provide a fundamental understanding of droplet flow on single and complex fiber networks. Essential to the project is the development of a new understanding of
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opportunity to join a multidisciplinary team at the intersection of AI and neonatal healthcare research, in a world leading network on research for improved newborn care. The candidate will collaborate with