Job Specifications
Join us as we transform immunology and deliver medicines that help autoimmune patients get their lives back. argenx is preparing for multi-dimensional expansion to reach more patients through a rich pipeline of differentiated assets, led by VYVGART, our first-in-class neonatal Fc receptor blocker approved for the treatment of gMG, and with the potential to treat patients across dozens of severe autoimmune diseases.
We are building a new kind of biotech company, one that maintains its roots as a science-based start-up and pushes our commitment to innovate across all corners of our business. We strive to inspire and grow our company, our partnerships, our science, and our people, because when we do, we deliver more for patients.
We are currently looking for a collaborative and scientifically curious Scientist, Integrated Discovery Biology to join our dynamic R&D team in our facility in Gent/Zwijnaarde. This role is positioned at the intersection of bioinformatics, immunology and therapeutic antibody discovery. You will partner closely with discovery scientists, antibody engineers, and quantitative scientists to translate novel target validation questions and discovery research project hypotheses into focused omics analyses and data-driven answers that directly influence our early stage pipeline.
Through multi-omics data analysis, integrating public and internal datasets, you will help shape the knowledge base of our therapeutic targets and support efficient, early decision-making to prioritize insourcing of novel projects as well as program progression towards development.
This role is ideal for someone who thrives in cross‑functional science, enjoys working with discovery scientists to tackle complex biological questions, can translate those questions into structured, data‑driven approaches, and is motivated by making a meaningful therapeutic impact.
This position is based at our facility in Zwijnaarde, Belgium, and expects on-site presence at least 4 days a week.
Work Description
Key responsibilities include
Integrated Biology & Data Science Support Partnership
Serve as the primary Data Science point of contact for discovery project teams. Partner with discovery project leads and data scientists to translate biological hypotheses into actionable computational strategies.
Interpret immunology and disease questions and pro-actively propose fit‑for‑purpose data sourcing, processing and analytical approaches. This all in close collaboration with project scientists to co-develop a strategy tailored to the biological question/hypothesis.
Determine and provide strategic direction of analytical feasibility and alignment of omics platforms with project decision needs. Co‑develop analysis plans covering immune‑cell characterization, target validation, MoA exploration, and integrated multi‑omics interpretation.
Collaborate with academic partners and CROs to support analysis of their datasets and harmonize approaches.
High‑Quality Multi‑Omics Analysis
Execute robust processing and analysis of bulk/scRNA‑seq, proteomics, genetics, and pathway/network datasets.
Integrate internal discovery data with public datasets to strengthen biological insights.
With support of data scientists, co-develop and maintain pipelines for data exploration, differential expression, cell‑state/pathway perturbations, ligand–receptor interactions, target prioritization, and tissue selectivity/safety assessments.
Ensure data quality, documentation, and scientific rigor in all computational workflows.
Insight Generation & Cross‑Functional Collaboration
Synthesize complex analyses into clear biological narratives and concise decision‑ready recommendations.
Partner with disease biologists to contextualize findings within disease mechanisms.
Deliver outputs such as validation evidence summaries, mechanistic visualizations, pathway biomarkers and go/no‑go recommendations.
Communication & Scientific Rigor
Communicate analytical findings clearly to multidisciplinary teams and scientific leadership on a regular basis.
Uphold high standards for data integrity, transparent reporting, and reproducibility.
Support collaborative and efficient ways of working by sharing best practices, aligning workflows with partners, and contributing to a strong data‑driven discovery culture.
Profile
Essential
Ph.D. with a strong and proven background in Immunology, Computational Biology and Bioinformatics . Experience in an industrial setting or with regular industry interaction is a plus.
Strong track record analyzing biological datasets (bulk RNA seq, scRNA seq, proteomics, immunomics).
Solid understanding of immunology or inflammatory biology, including immune cell populations and pathways. Experience in working in autoimmune or immune‑mediated diseases is of substantial added value.
Ability to work effectively with data scientists; familiarity with R, Python, or standard data analysis environments is a plus, though not required for primary responsibil