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Postdoctoral Fellow (Level 1 or 2) working on Digital Twin modeling of Childhood Cancer


Systems Biology Ireland, University College Dublin

Job Location

University College Dublin
Co. Dublin
D04 V1W8


€42,783 - €54,965

Job Description

University College Dublin (UCD) is seeking applications for a Postdoctoral Research Fellow to work on the construction of Digital Twins in order to address drug resistance and improve treatment responses in cancers of children and young adults (CAYA). The Digital Twins are computer models constructed from multiomics data obtained from cell lines, biological model systems, and patients. To construct the Digital Twin models we are using a combination of AI/ML and ODE based modelling.


The successful candidate will need to have solid knowledge and/or practical experience in at least one of the following areas: (1) bioinformatics, especially the analysis of genome sequencing, RNA sequencing, and/or proteomics data; (2) AI/ML methods, such as regression analysis, unsupervised and supervised ML, and neural networks. The Fellow should be self-motivated and comfortable working with collaborators from different disciplines including mathematical modelers, biologists and clinicians. The project involves collaborations with pediatric oncologists from Childrens Health Ireland and international sites. The post will be based in SBI at UCD and the successful applicant will be part of the Kolch Group.

How to Apply

Go to the Work at UCD website and search Job Reference 016964.

About Our Organization

Systems Biology Ireland, established in 2009, has successfully developed an integrated mathematical modelling and experimental research program focusing on the design of new therapeutic approaches to diseases, primarily cancer, based on a systems level, mechanistic understanding of cellular signal transduction networks. SBI uses mathematical and computational modelling approaches in combination with cutting edge experimental technologies including various omics methods. A main aim of SBI’s research is to develop digital twin models of cancer patients that open new avenues for understanding and treatment of human diseases on a molecular level.

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