Thesis supervisor: Csaba Kerepesi
Location of studies (in Hungarian): Számítástechnikai és Automatizálási Kutatóintézet Abbreviation of location of studies: ELTE
Description of the research topic:
Aging has a major impact on human health, economy and society in general, but its molecular basis remains poorly understood. Until recently, it was not possible to quantify progression through aging accurately enough to be useful for practical purposes. However, recent research suggests that omics technologies together with advanced bioinformatics and machine learning are capable to track the aging process by developing mathematical models („aging clocks”) that can estimate the chronological- and biological age of an individual. Aging clocks can predict the progression of age-related diseases, evaluate longevity intervention and recently emerged rejuvenation therapies. Classification of aging-related genes/proteins and network science also advance aging and rejuvenation biology. In summary, the candidate will analyse large public datasets, related to aging, by using advanced mathematics and informatics (e.g. data mining and machine learning) and draw conclusions.
Required language skills: English Further requirements: Excelent mathematics and informatics knowledge with interest in the aging and rejuvenation research.
Number of students who can be accepted: 1
Deadline for application: 2023-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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