PhD Position in Computational Methods for Digital Twins of Embryonic Development & Disease
Develop scalable algorithmic infrastructure and simulation environments for digital twins of biological systems.
Best for:Best for candidates with a strong background in computer science or applied mathematics who are eager to apply numerical methods and machine learning to biological systems.
Overview
The Computational Biology Group at ETH Zürich is seeking a PhD candidate to advance the development of digital twins for embryonic development and reproductive health. The project focuses on creating robust algorithmic infrastructure to handle high-dimensional, nonlinear models and noisy biological data. The successful applicant will work at the intersection of machine learning, scientific computing, and biology to build scalable simulation tools. This role involves close collaboration with experimentalists and clinicians to apply these models to real-world challenges, such as IVF treatment planning.
What you'll do
- Develop and benchmark algorithms for parameter estimation and uncertainty quantification.
- Implement and optimize simulation environments with a focus on scalability and reproducibility.
- Apply computational methods to imaging-based models of tissue development and hormonal cycles.
- Collaborate with experimentalists and clinical partners to integrate real-world data into models.
- Contribute to the group's open-source software projects.
- Publish research findings in peer-reviewed journals and present at international conferences.
- Participate in teaching activities within the department.
Requirements
Degree required: Master's degree in Computer Science, Computational Science and Engineering, Applied Mathematics, Physics, or a related field.
Degree offered: PhD
Language: Good written and spoken English.
Instruction: English
- Strong programming proficiency in Python, Julia, or C++.
- Experience in writing clean, well-tested, and maintainable code.
- Solid foundation in numerical methods, optimization, or statistical inference.
- Demonstrated interest in applying quantitative methods to biological or biomedical problems.
Funding & terms
How to apply
Applications must be submitted exclusively through the official ETH Zürich online portal. Please prepare a letter of motivation, your CV, academic transcripts, and contact details for two referees.
- Letter of motivation
- CV
- BSc diploma and transcripts
- MSc diploma and transcripts
- Contact details of 2 referees
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.