SciLifeLab awards the Pereira Lab in the Grant Call for Academic PhD Projects in Data-DrivenLife Science (DDLS)

The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) awarded the project “A virtual cellular reprogramming screening platform” to recruit a PhD student in the research area of Data-driven Cell and Molecular Biology.

A central part of the SciLifeLab community, the DDLS Research School aims to educate life science researchers in Sweden, focusing on projects that have a clear data science component, either developing or applying computational methods to tackle life science problems.

Reprogramming somatic cells into specific immune cell types holds significant promise for increasing knowledge of immune responses and advancing novel immunotherapies. The lack of understanding of how transcription factors (TFs) cooperate to specify diverse immune cell identities represents a major roadblock for immune cell reprogramming. Crucially, the full potential of data-driven computational approaches to advance reprogramming technologies remains to be realized.

We have recently developed REPROcode, a high-throughput screening platform that uses barcoded TFs and single-cell transcriptomics to identify TFs driving immune cell reprogramming. By leveraging the highly multiplexed dataset created with REPROcode, this project will extract induced immune cell fates/states and TF combinations, examining transcriptomes and barcoded TFs through the application of mathematical modelling techniques. The aims of this PhD project are the following: build and validate a reference atlas for reprogrammed immune cells, build a predictive model for immune cell identity, and model TF networks for immune cell reprogramming.

The selected PhD student will be supervised by Filipe Pereira, and co-supervised by our team member Ilia Kurochkin and by Fabian Theis from the Computational Health Center at Helmholtz (Munich, Germany). This role offers a unique opportunity to work at the interface of computational modeling and immune cell reprogramming.

Candidates with a strong interest in data-driven immune cell engineering, single-cell analysis, and mathematical modelling are encouraged to apply (here).