About the Project
We are looking for an enthusiastic and ambitious student to develop and apply sophisticated data-mining methods and computational models at the interface of biology, mathematics and computer science. The sequencing of genomes has opened unparalleled opportunities to compare multiple genomes and identify DNA sequences that modulate ageing in humans or determine species differences in ageing and longevity. There is also an urgent need to understand how genes associated with ageing collectively regulate the ageing process. We are analysing gene expression data and developing gene networks to deepen our knowledge of how genes interact with each other and with the environment to gain new insights into the genetics of ageing and identify new candidate genes for experimental validation. The exact direction of this project, however, will be adapted to fit the research interests of the student.
Though this project is primarily computational, our group also has wet lab facilities and thus it is possible to experimentally validate any computational predictions emerging from this project.
Training associated with this project:
This project will provide a rich and diverse training in contemporary bioinformatics techniques, genetics and biogerontology. The student will also obtain training in modern methods in genomics, including in the generation and analysis of high-throughput data from next-generation sequencing platforms.
In addition to the generic skills training that is provided through the Institute and University PhD programme, the student will be supported by an excellent infrastructure and will work closely with experts on the biology and genetics of ageing, bioinformatics and genomics. This diverse and stimulating environment will allow a creative and talented student to develop key skills and the project is flexible enough to allow the student to develop his or her own research interests. The student will be well-prepared for a successful career in research and in biotechnology.
The Institute of Ageing and Chronic Disease is fully committed to promoting gender equality in all activities. We offer a supportive working environment with flexible family support for all our staff and students and applications for part-time study are encouraged. The Institute holds a silver Athena SWAN award in recognition of on-going commitment to ensuring that the Athena SWAN principles are embedded in its activities and strategic initiatives.
To apply please send your CV and a covering letter to Joao Pedro de Magalhaes at [Email Address Removed] with a copy to [Email Address Removed]
Potential applicants are encouraged to contact Dr de Magalhaes in the first instance for an informal discussion.
The successful candidate should have an Honours Degree at 2.1 or above (or equivalent). Candidates whose first language is not English should have an IELTS score of 6.5 or equivalent.
Calvert S, Tacutu R, Teixeira R, Ghosh P, de Magalhães JP (2016) “A network pharmacology approach reveals new candidate caloric restriction mimetics in C. elegans.” Aging Cell 15:256-266.
Wood SH, van Dam S, Craig T, Tacutu R, O’Toole A, Merry BJ, de Magalhães JP (2015) “Transcriptome analysis in calorie-restricted rats implicates epigenetic and post-translational mechanisms in neuroprotection and ageing.” Genome Biology 16:285.
Keane M et al. (2015) " Insights into the evolution of longevity from the bowhead whale genome." Cell Reports 10:112-120.
Keane M et al. (2014) "The Naked Mole Rat Genome Resource: facilitating analyses of cancer and longevity-related adaptations." Bioinformatics 30:3558-3360.
Li Y & de Magalhães JP (2013) “Accelerated protein evolution analysis reveals genes and pathways associated with the evolution of mammalian longevity.” AGE 35:301-314.
Tacutu R et al. (2013) “Human Ageing Genomic Resources: Integrated databases and tools for the biology and genetics of ageing.” Nucleic Acids Research 41:D1027–D1033.
Wuttke D et al. (2012) “Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.” PLoS Genetics 8:e1002834.
Silva AS et al. (2011) “Gathering insights on disease etiology from gene expression profiles of healthy tissues.” Bioinformatics 27:3300-3305.
Freitas A et al. (2011) “A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related.” BMC Genomics 12:27.
TEDx talk by Dr de Magalhaes:
Further details about our work on ageing and age-related diseases are available at:
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