Publisher
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ETH Zurich

PhD Position in Computational Methods for Digital Twins of Embryonic Development and Disease ETH Zurich in Switzerland

Degree Level

PhD

Field of study

Computer Science

Funding

Competitive ETH doctoral salary and conditions; support for scientific development including conference travel and training.

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Country

Switzerland

University

ETH Zurich

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Keywords

Computer Science
Biomedical Engineering
Biology
Mathematics
Computational Biology
Statistical Inference
Computational Science
Uncertainty Analysis
High Performance Computing
Optimisation
Statistics
Physics
Applied Mathematic
Biomedicine
ML

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About this position

ETH Zurich is advertising a PhD position in Computational Methods for Digital Twins of Embryonic Development & Disease at the Computational Biology Group of Prof. Dagmar Iber in the Department of Biosystems Science and Engineering (D-BSSE), Basel, Switzerland.

The project sits at the interface of computer science, mathematics, biology, and biomedicine. The research aims to build the algorithmic infrastructure for digital twins of living systems, with applications to embryonic development, reproductive health, hormonal-cycle modeling, and IVF treatment planning. The work involves parameter estimation, uncertainty quantification, optimization, Bayesian inference, physics-informed neural networks (PINNs), scalable simulation software, and reproducible high-performance computation.

The successful candidate will work closely with modellers, experimentalists, and clinical collaborators, contribute to open-source simulation tools, publish results, present at international conferences, and support teaching activities. The position is ideal for someone with a quantitative background and a strong interest in applying computational methods to biological systems.

Eligibility highlights: a Master's degree in Computer Science, Computational Science and Engineering, Applied Mathematics, Physics, or a related field; strong programming skills in Python, Julia, or C++; experience in numerical methods, optimization, statistical inference, or machine learning; good English; and an interest in learning the biological background. Experience with PDE-based simulations, finite element methods, HPC, PyTorch, or JAX is an advantage.

Funding: competitive ETH doctoral salary and conditions, plus conference travel and training support.

Application: submit a motivation letter, CV, BSc and MSc diplomas/transcripts, and contact details for 2 referees via the online portal. Applications are reviewed on a rolling basis until the position is filled.

Funding details

Competitive ETH doctoral salary and conditions; support for scientific development including conference travel and training.

What's required

Master's degree in Computer Science, Computational Science and Engineering, Applied Mathematics, Physics, or a related quantitative field; strong programming skills in Python, Julia, or C++; experience with numerical methods, optimization, statistical inference, or machine learning; interest in biology and biomedicine; good written and spoken English. Experience with PDE-based simulations, finite element methods, high-performance computing, or deep-learning frameworks such as PyTorch or JAX is an advantage.

How to apply

Apply online through the ETH Zurich application portal with a motivation letter, CV, BSc and MSc diplomas/transcripts, and contact details of 2 referees. Questions should be directed to Prof Dagmar Iber by email; do not apply by email.

More information can be found here

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