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Job Zusammenfassung
In diesem Job entwickelst du datengetriebene Surrogatmodelle zur Beschleunigung physikalischer Simulationen für die Aneurysmenbehandlung, implementierst ML-Pipelines und evaluierst deren Genauigkeit und Effizienz.
Job Technologien
Deine Rolle im Team
- Develop data-driven surrogate models to replace computationally expensive physics-based simulations for aneurysm treatment, namely, computational fluid dynamics (CFD) and finite element modeling (FEM), enabling rapid, on-demand simulation of patient-specific treatment scenarios.
- Design and implement machine learning (ML) pipelines using full-fidelity CFD and FEM data, ensuring models generalize across patient geometries and device configurations.
- Integrate trained surrogate models into the broader in silico trial framework and evaluate their accuracy, robustness, and computational efficiency against full-fidelity simulations.
- Explore AI-based methods for treatment outcome prediction and device optimization, contributing to the framework's clinical decision-support capabilities.
- Collaborate closely with clinicians, scientists, and engineers to develop and validate cutting-edge simulation techniques.
- Lead and co-author scientific publications, and represent the project at international conferences.
Unsere Erwartungen an dich
Qualifikationen
- PhD in Computer Science, Applied Mathematics, Physics, Engineering, or a related field with a strong computational focus.
- Proficiency in Python and relevant ML frameworks (e.g., PyTorch, TensorFlow, JAX) is essential.
- Familiarity with CFD, FEM, or other numerical simulation methods is a significant advantage.
Erfahrung
- Strong practical experience in machine learning for scientific applications - including surrogate modeling, reduced-order models (ROM), or physics-informed machine learning (PIML/PINNs) - is the core technical foundation of the role.
- Experience with high-performance computing (HPC) environments is beneficial.
Unser Angebot
- The salary will be based on the German E13 TV-L scale (100%), if terms and conditions under collective bargaining law are fulfilled.
- A full-time employment, currently 38.5 hours/week; a part-time employment may be possible within the framework of certain working time models.
- Flexible working hours to accommodate individual needs.
- Interdisciplinary research at the intersection of medicine, physics, engineering, and computer science.
- A vibrant, international biomedical research group embedded within a university hospital setting.
Benefits
Work-Life-Integration
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Job Standorte
Das ist dein Arbeitgeber
Universitätsklinikum Schleswig-Holstein
Als eines der größten Krankenhauszentren Europas hat das Universitätsklinikum Schleswig-Holstein - UKSH - zusammen mit der Christian-Albrechts-Universität zu Kiel und der Stiftungsuniversität zu Lübeck die Aufgabe, internationale Spitzenforschung mit interdisziplinärer Krankenversorgung zu verbinden. Darüber hinaus ist es eine wesentliche Aufgabe des Zentrums, die Ausbildung kommender generationen von Ärzten sicherzustellen.
Description
- Unternehmensgröße
- 250+ Employees
- Unternehmenstyp
- Etablierte Firma
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- Hybrid, Onsite
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- Gesundheitswesen, Soziales
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Postdoctoral Position Machine Learning for Simulation Acceleration
- Ort
- Kiel
- Arbeitsmodell
- Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
