Associate Principal/Principal Computational Biologist

Ready to push the boundaries of drug discovery? This is your chance to join a cutting-edge biotech shaping the future with condensate biology—an entirely new frontier in human health. They’re looking for a visionary Associate Principal / Principal Computational Biologist to harness advanced analytics, AI, and biological insight to crack the toughest therapeutic challenges. If you live for big data, bold ideas, and impact, this is the role that lets you change the game.

This is no ordinary biotech—it’s an industry pioneer redefining what’s possible in drug discovery. With a mission to decode condensate biology and transform treatments for diseases long considered ‘undruggable’, they unite high-resolution biology, AI-driven insight, and bold scientific thinking. Backed by world-class investors and alliances with leading pharma, they offer a culture of innovation, inclusion, and scientific adventure. 

This is the kind of environment where your work won't disappear into a backlog or sit in a publication queue for years. Instead, your analyses will directly influence programme decisions, guide experiments and help accelerate the development of potentially life-changing therapies.

Qualifications & Experience:

• Ph.D. or equivalent in Computational Biology, Bioinformatics, or related field
• Proven track record in data-driven drug discovery and multi-omics integration
• Strong knowledge of biological systems and computational modeling

Responsibilities:
Be the driving force behind computational innovation:

• Build and deploy advanced algorithms for multi-omics and imaging data
• Model mechanisms of disease and compound effects to power precision discovery
• Partner with experimental teams to transform complex data into actionable breakthroughs
• Evolve the company’s AI-first platform to spearhead the next wave of novel therapies

Skills / Technical Competencies:

• Proficiency in Python, R, and statistical modeling
• Expertise in machine learning, data integration, and visualization
• Hands-on experience with NGS, proteomics, or large-scale biological datasets
• Knowledge of cloud-based computation & big data architecture

Nice to Haves:

• Familiarity with AI/ML pipelines in biopharma
• Experience with graph theory, systems pharmacology, or dynamics modeling
• Exposure to computational chemistry or physics-based simulations