The project aims to build AI methods that design cyclic peptides co-optimizing binding affinity, permeability, stability, and synthetic feasibility to enable oral delivery and replace parenteral biologics
Job Summary
The project aims to build AI methods that design cyclic peptides co-optimizing binding affinity, permeability, stability, and synthetic feasibility to enable oral delivery and replace parenteral biologics.
The PhD student will be integrated in both Stockholm University and AstraZeneca environments, benefiting from interdisciplinary collaboration and access to industrial datasets and expertise.
The Molecular AI department at AstraZeneca is a leading group applying AI to molecular design, with a vibrant team of scientists and extensive resources for drug discovery.
Matching Summary
The project aims to build AI methods that design cyclic peptides co-optimizing binding affinity, permeability, stability, and synthetic feasibility to enable oral delivery and replace parenteral biologics.
Skills & Requirements
Must-have
Molecular AI for peptide design
Proficiency in Python programming
Experience with modern deep learning models
Oral bioavailability and permeability modeling
Collaborative scientific communication
Nice-to-have
Peptide or macrocycle modeling experience
Familiarity with protein language models
Exposure to molecular simulation and MD
Workflow automation and HPC environments
Collaborative software development experience
Key Requirements
Master's degree or equivalent in relevant fields
Excellent written and verbal communication skills
Highly collaborative mindset
Application submitted by April 19th, 2026
Temporary position for 4 years starting September 2026