Wissenschaftliche/-r Mitarbeiter/-in – Postdoc (w/m/d)
Core
Developing predictive models and cardiovascular digital twins using mathematical modeling and AI to model perioperative risks and enable clinical decision support.
Role type
Postdoctoral researcher (IC)
Builds
Cardiovascular digital twins and hybrid prediction systems for patient-specific risk modeling
Domain
Healthcare / Biomedical Engineering / Data Science
Deliverable
production ML models
Required skills
Mathematical modeling, Machine Learning, Statistics, Python, PyTorch/TensorFlow, Reproducible workflows, Clinical decision support modeling
Preferred skills
Cardiovascular physiology, VVQ (Verification, Validation and Uncertainty Quantification), HPC/Cloud, C++/MATLAB/Julia, Clinical data handling
Technologies
Python, NumPy, SciPy, pandas, scikit-learn, PyTorch, TensorFlow, Git, Docker, MATLAB, Simulink, Julia, C++, OpenFOAM, COMSOL
Responsibilities
Develop, calibrate, and validate mechanistic and data-driven models; Build cardiovascular digital twins and simulation scenarios; Implement technical solutions using Python/MATLAB/Julia/C++; Publish results and contribute to grant applications; Supervise students and coordinate work packages; Ensure data privacy and ethical compliance
Seniority
Postdoctoral researcher (early career IC)