Symposium & workshop on inequalities in infectious disease dynamics at LSHTM in April 2026. We aim to will bring together leading researchers and practitioners to share ideas, discuss recent advances, and reflect on future directions. Details & application: iddconf.org/lshtm-sympos... Closing 21 Jan

We're advertising an MRC-LID PhD studentship on modelling measles outbreak risk in teenagers and adults, with me, @amsuffel.bsky.social and @rozeggo.bsky.social You'll design mathematical models using vaccine data and Electronic Health Records to analyse recent transmission patterns, get in touch!

🥳 Registration for abstracts for EuroCIM 2026 (Oxford) is now OPEN and the deadline for submissions is 9 January 2026: eurocim.org/oxford-2026/... 👉 Theme? “Causal inference in health, economic and social science” 👉 When? April 14-17 👉 Where? Oxford 👉 Register? eurocim.org/oxford-2026/...

Our next #datascience seminar takes place this afternoon. Details and how to join 🔽

Data & Statistical Science for Health, LSHTM@lshtm-dash.bsky.social · 10mo ago

🛌 Tomorrow Anna Sigríður Islind will discuss the Sleep Revolution project and using #AI machine learning to develop better diagnoses for obstructive sleep apnea #HealthData 🗓️ Tuesday 21 October, 14:00 BST 📍 LSHTM | Online Details ⬇️ www.lshtm.ac.uk/newsevents/e...

Join us next week for our #PublicHealth seminar on using casual inference in #epidemiology research for asthma & kidney disease #HealthData 🗓️ Tuesday 14 October, 12:50 BST 📍 LSHTM | Online Details ⬇️ www.lshtm.ac.uk/newsevents/e...

New paper in @annalsofim.bsky.social "50 ways to misinterpret clinical prediction models for treatment decisions” --> Published version: www.acpjournals.org/doi/10.7326/... --> Open access version: arxiv.org/pdf/2402.17366

The Risks of Risk Assessment: Causal Blind Spots When Using Prediction Models for Treatment Decisions | Annals of Internal Medicine

Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who have already receiv...

acpjournals.org

🚨 Next month, we’ll be hosting a one-day event on target-trial emulation and other frameworks, exploring the role and potential of observational data for evaluating the effects of interventions Open to everyone working in #datascience #biostatistics #clinicaltrials Get your ticket 🔽 bit.ly/TTE_25

HIRING! 2 PhD openings within the “Safe Causal Inference” consortium with experts from biostatistics, computer science, math, and epidemiology. You'll develop new methods to evaluate prediction algorithms that take the causal effect of treatments into account. 👉 www.lumc.nl/en/about-lum....

PhD Candidates Causal machine learning – Performance assessment of causal predictive algorithms | LUMC

Do you want to work on challenging problems within causal inference and contribute to algorithms that support treatment decisions for individual patients? As PhD candidate causal machine learning at t...

lumc.nl

🎫Registration open for 1-day hybrid event: “Target trial emulation and other frameworks: The role and potential of observational data for evaluating effects of interventions”. 📆26th June. tinyurl.com/dash-tte. Hosted by LSHTM Centre for Data & Statistical Science for Health. @lshtm-dash.bsky.social

Target trial emulation and other frameworks | LSHTM

Large scale observational data are increasingly available for healthcare research, including from electronic health records and disease registries. Target trial emulation (TTE) provides a framework

tinyurl.com

📆 SAVE THE DATE: 26 June 📆 for our 1-day event on “Target trial emulation and other frameworks: The role and potential of observational data for evaluating effects of interventions”, hosted by the Centre for Data & Statistical Science for Health (DASH) at LSHTM. @lshtm-dash.bsky.social

👋 Hi Bluesky. We’re the Centre for Data and Statistical Science for Health (DASH) at @lshtm.bsky.social We are the hub for data and statistical science in LSHTM, applying our expertise and data science resources to the biggest problems in global health Find out more about us 👇

3rd April, in London and online, come and hear @rlgrant.bsky.social talk about his new book with Gian Luca Di Tanna on Bayesian meta-analysis. Further details at www.lshtm.ac.uk/newsevents/e...

Demystifying Bayesian meta-analysis for researchers | LSHTM

Bayesian models offer a powerful framework for meta-analysis through their flexible and probabilistic treatment of uncertainty.There are several methodological challenges in evidence synthesis,

lshtm.ac.uk

www.lshtm.ac.uk/newsevents/e...

Excited to speak in the CAUSALab Methods Series tomorrow

We're still seeking candidates interested in causal inference and/or survival analysis for a postdoc position in Oslo. Deadline January 31. Please apply or forward this to anyone who might be interested! www.jobbnorge.no/en/available...

Four year postdoc position at the Oslo Centre for Biostatistics and Epidemiology (OCBE) (272144) | University of Oslo

Job title: Four year postdoc position at the Oslo Centre for Biostatistics and Epidemiology (OCBE) (272144), Employer: University of Oslo, Deadline: Friday, January 31, 2025

jobbnorge.no

Seminar series on ‘Causal Inference in Environmental Epidemiology’ hosted by the DASH Centre, with experts from Harvard, North Carolina State, and LSHTM. First seminar on 22 January (15:00 - 16:00). Info and links: www.lshtm.ac.uk/newsevents/e... #CausalInference #LSHTM #AirPollution #DataScience

Vacancy for a postdoc position. Improve the transparency of decision support algorithms by figuring out how we can quantify and communicate uncertainty in individual causal predictions. With Marleen Kunneman, Daniala Weir and me. Three more days to apply 👇 www.lumc.nl/en/about-lum...

Postdoc Biomedical Data Scientist / Biostatistician | LUMC

In this postdoc position at LUMC, you will work on groundbreaking research that enhances the transparency and trustworthiness of decision support algorithms in healthcare. This position allows you to ...

lumc.nl

📣 Do you want to learn about recent advances in causal inference? Colleagues at INSERM are organising a workshop gathering international experts in the field. Bonus: it's happening in two amazing locations 🌇🇫🇷

🔥Air pollution from landscape fires associated with over 1.5 million deaths globally per year. New research in The Lancet co-authored by Malcolm Mistry & Antonio Gasparrini from #EHMLab at LSHTM assessed the global impact of #AirPollution from landscape fires. #PublicHealth 👉 bit.ly/3R3LiZY

New paper from Shaun Seaman and me on how to simulate data from marginal structural models (MSMs) for survival outcomes, including Cox MSMs. This can be useful in simulation studies evaluating causal inference methods that use MSMs. R code provided. onlinelibrary.wiley.com/doi/10.1002/...

Simulating Data From Marginal Structural Models for a Survival Time Outcome

Marginal structural models (MSMs) are often used to estimate causal effects of treatments on survival time outcomes from observational data when time-dependent confounding may be present. They can be...

onlinelibrary.wiley.com