Postdoctoral Bioinformatician: AI-Driven Genomics

IRB Barcelona; España; On-site; EUR 42,000 - 64,000; Full time

Job summary

IRB Barcelona is seeking a talented Postdoctoral Researcher to join the Biomedical Genomics Lab (BBGLab) led by Dr. Núria López-Bigas.

You will work on developing AI-assisted systems to answer biological questions at scale and contribute to the co-development of agentic systems for human-AI scientific collaboration. The role focuses on tumorigenesis mechanisms across genes and tissues, with experience in LLMs and RAG/agentic systems considered a plus.

Qualifications

• PhD in Biomedicine or related field with strong biomedical data experience.
• PhD in Biomedical Informatics or Bioinformatics is advantageous.
• MSc in Bioinformatics/Computational Biology or related field preferred.
• Experience with machine learning and large-scale data analysis.
• Strong programming skills in Python or R; ability to work independently.

Responsibilities

• Independently design and test computational genomics analyses and interpret results.
• Collaborate with multidisciplinary team and external partners.
• Contribute to scientific excellence, efficiency, and teamwork.
• Maintain lab protocols and resources, and support other lab projects.
• Discuss analytical results and prepare diverse scientific communications.

Skills

Machine Learning

Python

R

Independent computational analyses

Communication

Collaboration

English proficiency

Education

PhD in Biomedicine

PhD in Biomedical Informatics

PhD in Bioinformatics

MSc in Bioinformatics

MSc in Computational Biology

Tools

Python

R

Job description

IRB Barcelona is seeking a talented Postdoctoral Researcher to join the Biomedical Genomics Lab (BBGLab) led by Dr. Núria López-Bigas.

You will work on developing AI-assisted systems to answer biological questions at scale and contribute to the co-development of agentic systems for human-AI scientific collaboration. The role focuses on tumorigenesis mechanisms across genes and tissues, with experience in LLMs and RAG/agentic systems considered a plus.