PhD in Multimodal ML for Longitudinal Preterm Lung Health

Laplace Expert Ltd; Basel; Hybrid; CHF 46,000 - 60,000; Full time

Job summary

University of Basel invites applications for a four-year PhD position in machine learning for preterm lung health. The project integrates longitudinal measures of lung growth, environmental exposure, and cohort data to predict long-term respiratory outcomes in children.

Candidates should hold an MSc in a quantitative field, be proficient in Python and ML libraries (PyTorch/scikit-learn), and have strong English; German is advantageous but not required.

Qualifications

• MSc in quantitative discipline and strong English; German advantageous but not required.
• Proficiency in Python and ML frameworks (PyTorch/scikit-learn) and statistical modelling.
• Experience with longitudinal and multi-modal data is desirable.

Responsibilities

• Develop interpretable ML models for longitudinal prediction.
• Handle missing data and temporal analyses with reproducible Python code.
• Collaborate with clinicians and researchers; publish findings and present at conferences.

Skills

Python

ML frameworks

Statistical modelling

English proficiency

Education

MSc in Computer Science, Data Science, Statistics, Biomedical Engineering or related field

Tools

PyTorch

scikit-learn

Job description

University of Basel invites applications for a four-year PhD position in machine learning for preterm lung health. The project integrates longitudinal measures of lung growth, environmental exposure, and cohort data to predict long-term respiratory outcomes in children.

Candidates should hold an MSc in a quantitative field, be proficient in Python and ML libraries (PyTorch/scikit-learn), and have strong English; German is advantageous but not required.