Within-Host Infectious Disease Modelling Scientist

SONICOM; Gloucester; On-site; GBP 42,000 - 65,000; Full time

Benefits offered by this job

41 days off a year

Generous pension schemes

Job summary

Imperial College London is seeking a Research Associate in infectious disease modelling to lead modelling efforts within a broad international collaboration focusing on novel immunological tools for surveillance of viral spillover. The role sits in the Centre for Global Infectious Disease Analysis and involves interaction with partners in the UK and Southeast Asia, with occasional travel.

The postholder will contribute to high‑level epidemiological modelling, collaborate across disciplines, and

Qualifications

• PhD in infectious disease epidemiology or a quantitative discipline.
• Experience in developing mathematical models, ideally within-host virus models.
• Experience reviewing and synthesising scientific literature.
• Ability to communicate technical results to varied audiences.
• Experience working in a multidisciplinary international environment.

Responsibilities

• Lead the Imperial College contribution focusing on within-host immune system modelling.
• Collaborate with international partners and interact with a diverse research team.
• Travel to the region as required to coordinate and support the project.

Skills

PhD in infectious disease epidemiology

Mathematical modelling

Statistics

Within-host models for viruses

Literature review

Scientific communication

Multidisciplinary collaboration

Education

PhD in a relevant quantitative field

Job description

Imperial College London is seeking a Research Associate in infectious disease modelling to lead modelling efforts within a broad international collaboration focusing on novel immunological tools for surveillance of viral spillover. The role sits in the Centre for Global Infectious Disease Analysis and involves interaction with partners in the UK and Southeast Asia, with occasional travel.

The postholder will contribute to high‑level epidemiological modelling, collaborate across disciplines, and