Postdoctoral Fellow on Biological Data Sciences (ref. PD/24/04)

IRB Barcelona is seeking a talented and highly motivated Postdoctoral Researcher to join the Structural Bioinformatics and Network Biology group (, led by Dr. Patrick Aloy, to work on Systems Medicine approaches in the context of the CLARITY European collaborative project.

Viral infections, together with human genetics, constitute major risk factors for developing complex diseases. However, the molecular and physiological mechanisms of how these viral infections cause and contribute to non-communicable disease development are unknown thus hampering prevention and therapeutic approaches. CLARITY will take advantage of cutting-edge experimental technologies and artificial intelligence (AI)-driven analytics to elucidate the molecular and physiological mechanisms of how RSV infection (infectious disease) contributes to asthma (non-communicable disease) development.

In particular, we will use modern AI techniques to integrate the generated RSV data with the bulk of current biomedical knowledge and derive RSV perturbation signatures. We will then compare these signatures to those of non-communicable human diseases, and implement a strategy to discover causal relationships between them. Finally, we will identify and validate drug-like molecules with the potential to revert the RSV perturbation induced changes in vitro, and provide initial lead compounds for further development.

This position is co-financed by the project "Causative Link between respirAtory syncytial viRus and chronic lung diseases: Identifying Targets for therapY" (CLARITY) form the EU Horizon Europe programme. Grant Agreement nº 101137201.


The successful candidate will work in a very collaborative environment, where he/she will be responsible for the integration of all the generated data into the embeddings space of the Chemical Checker (Duran-Frigola et al. Nat Biotechnol 2020; Bertoni et al. Nat Commun 2021) and the Bioteque (Fernández-Torras et al. Nat Commun 2022) as well as the development of the new signatures to define the perturbed modules. Additionally, he/she will also be responsible for developing the comparative methods to link the effects of viral-perturbations to the signatures of non-communicable common diseases. Finally, he/she will adapt the generative-AI models available in the group to identify or design new chemical compounds with the capacity to stop the progression from RSV-induced cellular perturbations to the onset of related non-communicable diseases.


Must Have – Required:

Education: Engineering degree in Computer, Data Sciences or a bachelor in Biosciences. PhD in bioinformatics, data sciences, machine learning or related areas.
Experience: Previous experience on the use of machine learning and data science techniques. Strong publications record according to his/her career stage.
Excellent programming and scripting skills, with deep knowledge of Python.
Excellent knowledge of machine learning packages (Scikit, Keras, Pytorch, etc).
Competent in the use of HPC systems, virtual machines (OpenNebula) and Grid Containers (Docker, Singularity).
Excellent interpersonal and communication skills. Highly motivated. Fluency in English.


Experience: Previous experience working with knowledge graphs (KG) and embedding techniques, as well as with biological data and in an international environment.
Skills: Knowledge of AI-based generative models (e.g. VAEs, GANs, Diffusion models, etc)