Postdoctoral Fellow On Molecular/cell Biology - Barcelona, España - Somm Excellence Alliance

Somm Excellence Alliance

Empresa verificada

Barcelona, España

hace 2 semanas

Publicado por:

Isabel García

beBee Recruiter

Descripción

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

DUTIES:

EXPERIENCE, KNOWLEDGE, SKILLS:

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.
Skills:

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.

Desirable:

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)

Deadline:
March 15, 2024

Job category:
Postdoc

Area:
Life Sciences