About the role
AI summarisedPostdoctoral research role focused on using all-atom molecular dynamics simulations to study pH-dependent conformational dynamics of coronavirus spike proteins across variants, aiming to inform vaccine design and diagnostics.
ResearchOnsiteBioinformatics Institute
Key Responsibilities
- Investigate the pH-dependent structural dynamics and receptor-binding behaviour of coronavirus spike proteins across multiple variants
- Understand how environmental conditions such as pH influence spike protein conformational states, ACE2 binding, and viral infectivity
- Integrate all-atom molecular dynamics simulations, structural modelling, and quantitative analysis of biomolecular interactions
- Characterise how spike proteins from SARS-CoV-2 variants respond to physiologically relevant pH conditions
- Study how protonation states and environmental factors drive conformational transitions, structural stability, and compaction or aggregation behaviour
- Analyse how these changes modulate receptor recognition and immune evasion
- Extend principles of pH-dependent protein dynamics to complex viral systems
- Perform comparative analysis across variants
- Integrate experimental collaborations to validate predicted structural and functional changes
- Generate mechanistic insights to inform variant-adapted vaccine design, improved diagnostics, and preparedness for future coronavirus outbreaks
Requirements
- PhD in computational chemistry, computational biophysics, computational biology, or a related discipline
- Extensive experience in all-atom molecular dynamics simulations of biomolecular systems
- Analysis of protein structural dynamics, conformational transitions, and stability under varying environmental conditions (e.g. pH, ionic strength)
- Experience in studying biomolecular binding interactions, including protein–protein, protein–receptor, or protein–ligand systems
- Ability to analyse and interpret binding modes, interaction networks, and structural determinants of molecular recognition
- Strong ability to interpret simulation results in a biological and mechanistic context
- Experience with simulation packages (e.g. GROMACS, AMBER, CHARMM) and associated analysis tools
- Familiarity with enhanced sampling methods or binding free energy approaches (e.g. MM/PBSA or related techniques)
- Experience in trajectory analysis and handling large-scale simulation datasets
- Scripting/programming skills (e.g. Python, Bash) for data analysis and workflow automation
- Experience collaborating on interdisciplinary or experimental-led projects
- A strong publication record in computational biomolecular research or molecular simulation studies is advantageous