Postdoc: Co-Folding AI for Structure-Based Drug Discovery

Johnson Johnson; Beerse; On-site; EUR 42,000 - 60,000; Full time

Job summary

Johnson & Johnson is recruiting a Postdoctoral Scholar in Beerse, Belgium for In Silico Drug Discovery. You will work on co-folding models, structure-based drug discovery, and AI/ML applications, joining a multidisciplinary team in Therapeutics Discovery.

The role focuses on data curation, training, benchmarking, and integration into discovery workflows, with opportunities for collaborations across CADD, biologics, and AI/ML groups.

Qualifications

• PhD in computational chemistry, structural bioinformatics, computational biology, or ML for biomolecular systems.
• Strong understanding of protein structure and structure-based modeling concepts.
• Experience with AI/ML model development, training, fine-tuning, and evaluation (e.g. PyTorch).
• Experience generating or working with structural datasets (protein–ligand, protein–protein, MD-derived data).
• Experience coding and developing research workflows in Python.
• Familiarity with HPC and GPU computing environments.
• Strong analytical, problem-solving, and scientific communication skills.
• Track record of scientific deliveries including peer-reviewed publications and presentations.
• Professional fluency in English.
• Up to 10% travel domestically and internationally.

Responsibilities

• Design, run, and analyze fine-tuning experiments for co-folding and structure-prediction models, benchmarking against baselines.
• Generate, curate, and manage training/validation datasets to support fine-tuning and evaluation.
• Assess model performance using structural and task-relevant metrics; contribute to evaluation best practices.
• Integrate fine-tuned co-folding models into end-to-end discovery workflows from inference to reporting.
• Collaborate with In Silico Discovery scientists across CADD, biologics, and AI/ML teams.
• Contribute to internal communication, documentation, and publication-ready summaries.

Skills

Python programming

AI/ML model development

PyTorch

Computational chemistry

Structural bioinformatics

English fluency

Education

PhD in computational chemistry or related field

Tools

HPC environments

GPU computing

Version control

Job description

Johnson & Johnson is recruiting a Postdoctoral Scholar in Beerse, Belgium for In Silico Drug Discovery. You will work on co-folding models, structure-based drug discovery, and AI/ML applications, joining a multidisciplinary team in Therapeutics Discovery.

The role focuses on data curation, training, benchmarking, and integration into discovery workflows, with opportunities for collaborations across CADD, biologics, and AI/ML groups.