Pulmonary research is evolving. With the continuous growth of high-throughput imaging and genomics technologies, and the organization of patients into large cohorts, massive amounts of data are being generated to address critical questions in pulmonary health today. Uncovering disease mechanisms, identifying early prognostic signals, or evaluating the effects of novel drug compounds all require finding robust, generalizable patterns from large datasets. In this era of big data, mathematical and statistical literacy, as well as computational skills are becoming indispensable for advancing pulmonary science. DataLung aims to promote these skills among lung scientists by providing PhD candidates, postdocs, and clinician scientists with the necessary training to excel in the era of big data.
DataLung is a joint venture between the DZL Academy and the Artificial Intelligence and Digital Tools disease-spanning working group. It is set up as an umbrella organization around existing PhD schools across the DZL sites. DZL members can apply to join DataLung to work towards completing a certificate in data science for pulmonary research. Joining DataLung comes with:
DataLung is targeted at DZL academy members who are looking to use or develop computational methods in their projects. This can range from analysing some of the data that they generate themselves to building new computational tools or infrastructure to analyse lung data. All candidates should have at least basic programming skills in Python, which can be deepened during the training program. In order to provide training that is suitable to candidates with different backgrounds, courses are initially divided into two tracks: The BIOTRACK and the COMPUTRACK.
The BIOTRACK targets DZL Academy with experimental or clinical backgrounds who have a good grasp of biological or clinical questions, but are missing the numerical training to analyse their own data. PhD candidates should have joined a basic Python course before starting the training program.
The COMPUTRACK targets DZL Academy members who have completed a numerical master’s degree (e.g., maths, stats, physics, engineering, computer science, or computational biology) or have otherwise received training in numerical disciplines. Candidates should feel comfortable analysing data, and may have experience in method development. While programming courses are on offer in the course book, no additional programming courses are foreseen for this track.
Applying to DataLung is a simple, two step process: first make sure you fulfill the enrollment criteria for the track you’re applying for, and then send the application documents to datalungschool@dzl.de.
In brief the enrollment criteria are:
The application template can be found here, and encompasses:
Please submit your complete application via email to datalungschool@dzl.de until February 21st, 2025. Please include your supervisor in CC in this email. Your supervisor must send her/his consent in a brief confirmation email. Finally, make sure that you are already a Fellow of the DZL Academy – if not, just follow the simple registration process on the DZL Academy webpages.
Your application will be screened by an expert review committee consisting of two representatives per site. Successful applicants will be notified via email by March 18, 2025.
DZL DataLung School Organizing Team:
![]() Malte Lücken, CPC-M |
![]() Doreen Franke, CPC-M |
![]() Rory Morty, TLRC |
![]() Svenja Gaedcke, BREATH |
![]() Jan Fuge, BREATH |
![]() Inke König, ARCN |
![]() Raphael Majeed, UGMLC |