Bioinformatics AI Scientist: LLM Tools & Agentic Workflows

VIB; Vlaams-Brabant; On-site; EUR 70,000 - 100,000; Full time

Benefits offered by this job

Flexible working hours

Salary in line with VIB scales

Indefinite contract

Job summary

VIB in Leuven invites a Data Scientist to build and deploy LLM-based tools supporting cancer biology research. You will create agentic workflows, connect tools to pipelines and HPC, and ensure reliability and data privacy. Collaboration with ML Unit, VSC, and internal teams is essential.

The role emphasizes training researchers, benchmarking methods, and keeping up with AI advances to responsibly apply AI in genomics and multi-omics analyses.

Qualifications

• PhD in Bioinformatics, Computational Biology, Computer Science, or related field (or equivalent experience).
• Strong Python programming skills and software development practices.
• Hands-on experience with LLMs via APIs or open-weight models.
• Familiarity with common bioinformatic workflows (sequencing, single-cell, spatial).
• Ability to explain AI concepts to non-specialists.
• Good English communication and collaboration skills.

Responsibilities

• Build LLM-based tools and agentic workflows for bioinformatics tasks.
• Connect LLM tools to pipelines, HPC, databases, and public resources.
• Evaluate tool reliability, correctness, reproducibility, and data privacy.
• Deploy and maintain tools with the ML Unit and VSC collaboration.
• Stay up to date with state-of-the-art methods in LLMs and computational biology.
• Deliver training and workshops on responsible AI use in research.

Skills

PhD in bioinformatics

Python

LLMs experience

Bioinformatics workflows

English communication

Education

PhD or equivalent

Tools

LangGraph

Open-weight models

HPC environments

Job description

VIB in Leuven invites a Data Scientist to build and deploy LLM-based tools supporting cancer biology research. You will create agentic workflows, connect tools to pipelines and HPC, and ensure reliability and data privacy. Collaboration with ML Unit, VSC, and internal teams is essential.

The role emphasizes training researchers, benchmarking methods, and keeping up with AI advances to responsibly apply AI in genomics and multi-omics analyses.