PhD Position in Statistical Machine Learning for Self-Driving Microscopy
at the University of Bern, Switzerland
Your Environment
You will be part of two complementary research communities:
- Pertz Lab -- Institute of Cell Biology (ICB)
A leading group pioneering real-time control of cellular signaling dynamics using microscopy, quantitative imaging, and optogenetics. This interdisciplinary team maintains close ties with engineering and data science.
- Ginsbourger Group -- Institute of Mathematical Statistics and Actuarial Science (IMSV)
Internationally recognized for its expertise in Gaussian process modeling, Bayesian optimal design, and machine learning for scientific discovery. The group fosters strong collaborations across mathematics, machine learning, and applied sciences.
You will regularly move between both labs, gaining fluency in communicating across disciplines—a valuable asset for your career.
Project Overview
Cells sense, integrate, and respond to dynamic stimuli through complex signaling networks. The Pertz Lab has developed powerful optogenetic tools and fluorescent biosensors that permit direct perturbation and measurement of these networks using light. Collaborating with the Ginsbourger Group, we aim to create autonomous, "self-driving" microscopes that:
- Build statistical models of biological dynamics in real time
- Predict the most informative next experiment
- Execute experiments automatically on living cells
Key methods utilized in this project will include:
- Gaussian Processes (heteroscedastic & multivariate)
- Operator-valued and deep kernels
- Active Bayesian experimental design
- Physics-informed neural networks
- Closed-loop control of biological systems
This project offers a unique opportunity to translate mathematical models into real-time guidance for experiments. Additionally, the position includes minor teaching responsibilities in Statistics, which come with an enhanced salary compared to standard PhD funding in Switzerland.
Why Choose Bern?
- Top-ranked Swiss research university
- International community and high quality of life
- Easy access to Europe
- Outstanding support for early-career researchers
Your Profile
- Master's degree in Mathematics, Statistics, Computer Science, or Engineering
- Solid skills in statistical modeling and probability theory
- Experience in coding (Python, R, Julia, Matlab, etc.)
- Motivated to work closely with experimental researchers
- Curiosity about biological systems; prior wet-lab experience is not required!
Application
Apply online using the form below. Only applications matching the job profile will be considered.