Thesis Work, 30 Credits – Ligand-AI Protein Reagents and RP3Net

About the role

AstraZeneca is offering a 30-credit master's thesis placement in Gothenburg, Sweden, focused on supporting the Ligand-AI project. You will produce recombinant proteins in E. coli, generate data to evaluate and improve protein expression prediction models such as RP3Net, and combine hands-on laboratory work with data analysis. The position is on-site, and the company does not provide accommodation.

Key responsibilities

• Express, purify and quality-check recombinant proteins in E. coli for screening in the Ligand-AI project.
• Investigate how codon optimization strategies and expression conditions affect production across 97 constructs.
• Analyze experimental results against predictions from RP3Net and other internal models and suggest improvements.
• Contribute high-quality protein reagents to an AI-driven drug discovery project.

Required profile

• Enrolled in a Master's programme in biochemistry, biotechnology, molecular biology, protein science or a related field.
• Previous lab-based experience with recombinant protein production in E. coli.
• Experience expressing recombinant proteins in E. coli and purifying them, ideally with nickel Ni-NTA chromatography.
• Interest in protein science, experimental data analysis, FAIR data capture and AI or computational models in biology.
• Excellent English, including scientific writing and presentation.