The BioSys PhD  Program is offering a PhD scholarship for the project: "What are the determinants of human genetic individuality?"The graduate will have the opportunity to work with world-leading researchers from BioISI (BioSystems and Integrative Sciences Institute) and LaSIGE at the University of Lisbonunder the supervision of Prof. Francisco Couto (LASIGE) and Prof. Margarida Gama-Carvalho (BioISI)

Applications until October 21st (12PM, CET)

How to apply:

Objectives: With the conclusion of the human genome project and the advent of next-generation sequencing, research on the human genome advanced towards a deeper understanding of human population diversity, focusing primarily on the identification of common genetic variants. With this project we want to evolve from studying the diversity within a population to the individual. We aim at establishing a measure for genomic similarity (involving both the sequence and structural levels) between an individual genome and a single or group of genomes.  Genomics information can spell much more about an individual than thought in the last decades, but the complexity of human behaviour is enormous and the determinants of human genetic individuality may be hard to predict from single genomic properties. This project will follow a systems biology approach to reach for a deeper understanding of the complexity of the human genome by analysing what defines us as individuals. The main goal is to understand how well we can predict if one specific person belongs to a group (for example, defined by a phenotype) by only using genomics data. The results generated by this project will be based on the intensive analysis of human sequencing datasets. By identifying the determinants of human genetic individuality, we will also be able to address some of the current concerns regarding the preservation of individual privacy when addressing the prominent necessity for data sharing [1]. 

[1] Cogo, V. V., Bessani, A., Couto, F. M., & Verissimo, P. (2015, October). A high-throughput method to detect privacy-sensitive human genomic data. In Proceedings of the 14th ACM Workshop on Privacy in the Electronic Society(pp. 101-110). ACM.

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