PhD Candidate Translational Bioinformatics and Statistics Healthy Aging

Chronological age is an important risk factor for nearly all types of common disease prevalent in our western society. Yet major inter individual differences are observed in the time spent in good health. As a PhD candidate working in the section Molecular Epidemiology (www.molepi.nl) within the department of Biomedical Data Sciences, you will perform omcis-driven research into the molecular determinants and predictors of healthy ageing. For this purpose you will develop and apply novel methodology for the integrative analysis of various types of high dimensional molecular data sources (genetics, transcriptomics, DNA-methylomics, metabolomics) measured within the Leiden Longevity Study, (www.leidenlangleven.nl) and within the BBMRI consortium (www.bbmri.nl/omics). The project will be performed in close collaboration with the Leiden Computational Biology Center (www.lcbc.nl), led by Prof. Reinders, with a strong link to the section of Pattern Recognition and Bioinformatics of the University of Technology in Delft.

Why is it that some persons remain healthy up to the highest ages whereas others require treatment for diseases like cardiovascular disease or type II diabetes from middle age onward? Within molecular epidemiology, we study the molecular changes that occur with ageing with the aim of identifying holistic indicators of declining health. You will work on large molecular data resources and will develop methods for the identification of patients at-risk of age-related disease. In addition, you will disseminate your work by writing scientific manuscripts and presenting your research at international conferences. The combination of this work will get you a PhD title.

What we ask
You hold a MSC degree in Bioinformatics, Statistics, Life Sciences or a similar field. Experience of techniques derived from data sciences, including cluster analysis, dimensionality reduction and predictive models are required. You must be familiar with a scripting language such as R or Python and with basic epidemiological concepts. Knowledge of genetic associations studies, heritability analyses and transcriptomic studies are favoured but not required. You enjoy gaining, combining and translating knowledge from multiple fields and have an optimistic and kind nature.

The department
The department of Biomedical Data Sciences including the section of Molecular Epidemiology holds an excellent track record on medical and macular statistics. In addition, you will be embedded at the Leiden Computational Biology Center, a group of scientists who aim to apply the state-of-the-art techniques from data science in the medical and biological domain.

Make sure to check out the website of our Graduate School: https://www.lumc.nl/org/graduate-school/?setlanguage=English&setcountry=en