_{06th January, 2026}

Head of AI/ML
Uk TechBio

We are seeking a senior leader to define and drive our foundation-model strategy for functional genomics. You will lead the design of novel multimodal architectures across omics and clinical data, build and mentor a world-class research team, and translate cutting-edge ML into biological insight and impact.

Research & Technical Leadership

• Define the research agenda for foundation models in functional genomics
• Design novel architectures for multimodal data (genomics, transcriptomics, proteomics, clinical)
• Develop self-supervised and representation learning methods for biological data
• Lead research on transformers and graph neural networks for biological systems
• Co-design architectures with the Causal & Mechanistic AI team to support causal identifiability
• Set standards for evaluation, reproducibility, and biological validity

Team & Collaboration

• Hire, mentor, and grow a high-performing ML research team
• Partner closely with computational biology teams and external academic collaborators

Applied Impact

• Apply foundation models to target identification, biomarker discovery, and patient stratification
• Guide build vs adapt vs buy decisions for models and tooling

Ideal Background

• PhD in ML, Computer Science, Computational Biology, or related field. PLUS several years of post study industry experience.
• Strong publication record in top ML or computational biology venues
• Deep experience with foundation models, self-supervised or representation learning
• Strong knowledge of transformers, geometric deep learning (GNNs), or variational methods
• Experience with multimodal learning and large-scale model training (PyTorch or JAX)
• Proven research impact (e.g. multiple publications at NeurIPS/ICML/ICLR/Nature Methods or similar)
• Must have experience, recruiting, mentoring and leading high performing ML teams

Domain Experience (Preferred)

• Hands-on experience with omics and/or clinical data
• Understanding of functional genomics concepts (e.g. GWAS, gene regulation, pathways)
• Familiarity with biological validation of ML models

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  



  
  
  
  
  
  
Keywords: AI / ML / Machine learning / artificial intelligence / foundation models / genomics foundation models / self-supervised learning / representation learning /  patient representation learning / perturbation modelling / leader / leadership / strategy / strategic / techbio / biotech / biology / biological / biotechnology

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