PhD and Postdoc positions in AI for biomedical discovery

Hayat Lab is seeking: PhD Students / Postdoctoral Researchers (m/f/d)

Shape the future of AI-driven biomedical research

We are seeking outstanding PhD students and Postdoctoral Researchers to join our work at the intersection of single-cell spatial omics, foundation models, AI agents, computational biology, and drug discovery. We develop computational methods that turn single-cell and spatial omics data into an understanding of human disease and into new therapeutic targets, with AI systems that are explainable and grounded in biological knowledge.

Research Focus

You will contribute to the development of new AI methods that combine:

  • Single-cell and spatial transcriptomics
  • Large language models, AI agents and multimodal foundation models
  • Gene regulatory networks, biomedical knowledge graphs and patient-level representations
  • Target discovery and drug development

Our research aims to move beyond black-box prediction towards explainable, mechanism-aware AI capable of supporting scientific reasoning and experimental design.

Key Responsibilities

  • Develop machine learning and AI methods for single-cell and spatial omics data and apply them to human disease
  • Develop multi-agent AI systems for biomedical hypothesis generation and target discovery
  • Integrate multimodal biological data with mechanistic knowledge and foundation models
  • Develop rigorous evaluation frameworks and open benchmarks for AI-assisted scientific discovery
  • Publish results in leading AI, computational biology, and biomedical journals and conferences

Candidate Profile

  • PhD Applicants: MSc in Computer Science, AI, Bioinformatics, Computational Biology, Statistics, or a related field.
  • Postdoctoral Applicants: PhD in AI, Machine Learning, Computational Biology, Bioinformatics, Systems Biology, or related disciplines

Desired Skills

  • Strong programming skills (Python)
  • Machine learning and deep learning (generative AI, causal modelling, or multimodal learning)
  • Experience with single-cell, spatial omics, systems biology, or biomedical data analysis is advantageous

We Offer

  1. A highly interdisciplinary and collaborative research environment
  2. Access to large scale single-cell and spatial transcriptomics datasets
  3. State-of-the-art computational drug-discovery workflows
  4. Opportunities to work at the intersection of single-cell spatial omics, foundation models, AI agents, computational biology, and drug discovery
  5. International collaborations
  6. Competitive salary and benefits according to institutional guidelines

Apply

Please submit a CV, brief motivation letter, and relevant supporting documents to shayat@ukaachen.de

Join us in building explainable AI systems that accelerate biomedical discovery and transform our understanding of human disease

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