The MND Association is in search for an experienced Epidemiological Consultant to support a national review of incidence and prevalence estimates for the association in the UK.

In this high impact collaborative post, you will reconcile variation across key datasets, including the MND Register, Hospital Episode Statistics (HES)–derived datasets, and the MND Association’s internal database.

You will work closely with the MND Register team at King’s College London and Oxford University, and be comfortable working with complex population health data in secure research environments.

If you would like to support MND and bring your expert epidemiological and statistical insight to produce a validated, national prevalence estimate, this role could be for you.

Key Responsibilities

Conduct a detailed audit of multiple datasets to assess structure, completeness, and consistency
Identify and address differences in case definitions, coding practices, and inclusion criteria
Develop and document a harmonised analytical framework for comparing datasets
Define and standardise MND case definitions, including consideration of subtypes and uncertain diagnoses
Align cohorts across data sources to enable meaningful comparison
Design and apply approaches to identify duplication and overlap within and between datasets
Incorporate mortality and survival data to refine prevalence estimates
Assess the feasibility and application of capture–recapture or similar completeness methods
Produce sensitivity analyses and low, central, and high prevalence scenarios
Clearly document assumptions, limitations, and interpretation of findings
Deliver reproducible, well‑documented analytical code within the KCL Trusted Research Environment
Produce both technical reports and senior‑level summary outputs for key stakeholders

All work will be undertaken within the King’s College London Trusted Research Environment (TRE), in line with governance and disclosure control requirements.

The King's College London - Computational Research, Engineering and Technology Environment (CREATE) Trusted Research Environment (TRE) hosts the data within https://docs.er.kcl.ac.uk/CREATE/TRE/tre/

The TRE itself is ISO 27001 certified and undergoes annual external audits and third-party penetration testing, ensuring ongoing compliance with international information security standards. The following programmes are available within the TRE for analysis; R studio, IBM SPSS, Anaconda, Stata and pgADmin for SQL.

About You

Advanced expertise in epidemiology, biostatistics, or health data science
Strong experience applying advanced statistical methods, such as capture–recapture or similar approaches
Proven experience working within secure data environments (e.g. Trusted Research Environments, NHS Digital, ONS Secure Research Service)
Strong analytical programming skills, with proficiency in R and/or Python
Experience working with large, complex health or population‑level datasets
Ability to clearly document methodology and communicate findings to both technical and senior audiences

The full consultant brief is attached.

About Us

Motor Neurone Disease moves fast. It takes away time, it takes away independence and it has no cure. Every day we support people affected by MND. We fund ground-breaking research. We campaign for better care. We’re here for everyone who needs us. Because with MND, every day matters.