University of Basel
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PhD Position in Machine Learning for Preterm Lung Health University of Basel in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
The position is a 100% four-year PhD employment at the University of Basel, with employment conditions in accordance with the University of Basel. The post mentions access to HPC infrastructure, graduate-school training, and conference opportunities, but does not specify a salary, stipend amount, or explicit tuition coverage.
Country
Switzerland
University
University of Basel
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About this position
PhD Position in Machine Learning for Preterm Lung Health
The Department of Biomedical Engineering at the University of Basel, through the Analytics & Informatics for Child Health group in collaboration with University Children’s Hospital Basel, invites applications for a 100% PhD position starting in November 2026 or by agreement. The appointment is for four years.
The project focuses on prematurity-associated lung disease and aims to develop a continuous, physiology-based risk-stratification framework to improve on categorical bronchopulmonary dysplasia definitions. Using the Basel-Bern Infant Lung Development cohort, the PhD researcher will integrate clinical history, infant lung function, breath metabolomics, urine oxidative-stress biomarkers, high-resolution air-pollution exposure, and longitudinal lung-function data extending from infancy to adolescence.
The successful candidate will lead the machine-learning component, developing multimodal models to identify early-life signatures, aetiotypes, and treatable traits of preterm lung disease. Responsibilities include modelling lung-function trajectories, analysing moderate-to-late preterm children, performing external validation with cohorts from Italy and Australia, publishing in machine-learning and clinical or respiratory venues, and producing reproducible code in collaboration with clinicians, epidemiologists, and exposure scientists.
Applicants should have an MSc in Computer Science, Data Science, Statistics, Biomedical Engineering, or a related area, along with strong Python skills and experience with PyTorch, scikit-learn, statistical modelling, longitudinal or tabular data, missing data, and model validation. Interests in interpretable machine learning, clustering, phenotyping, time-series analysis, clinical research, respiratory health, or pediatric medicine are welcome. English fluency is required; German is an advantage.
The position offers access to a unique longitudinal birth cohort, international validation datasets, HPC infrastructure, close interdisciplinary supervision, and enrolment in the Graduate School Medical and Health Sciences. Applications should be submitted as one PDF through the University of Basel application portal and include a CV, one-page cover letter, degree transcripts, and two to three references.
Funding details
The position is a 100% four-year PhD employment at the University of Basel, with employment conditions in accordance with the University of Basel. The post mentions access to HPC infrastructure, graduate-school training, and conference opportunities, but does not specify a salary, stipend amount, or explicit tuition coverage.
What's required
Applicants should hold an MSc in Computer Science, Data Science, Statistics, Biomedical Engineering, or a related field. Requirements include solid Python programming skills, fluency with machine-learning frameworks such as PyTorch and scikit-learn, statistical modelling experience, and experience with tabular or longitudinal data, missing data, and model validation. Experience with small-sample or clinical/epidemiological data is advantageous. Interest in interpretable machine learning, clustering or phenotyping, time-series or trajectory modelling, clinical research, respiratory health, or pediatric health is desirable. Applicants should demonstrate rigour, independence, and the ability to communicate with non-technical collaborators. Fluency in spoken and written English is required; German is advantageous but not required. The application must include a CV, a maximum one-page cover letter, MSc and BSc transcripts, and contact information for two to three references; links to GitHub, a thesis, or previous technical work are optional.
How to apply
Prepare one PDF containing your CV, a maximum one-page motivation letter, MSc and BSc transcripts, and contact details for two to three references. Submit the PDF through the University of Basel application portal: https://career2.successfactors.eu/career?company=unibas&career_ns=job_application&career_job_req_id=6945.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.