PhD Student / PhD Student

PhD Position in Statistical Machine Learning for Self-Driving Microscopy

Location

University of Bern, Switzerland

Your Environment

You will be integrated within two complementary research communities:

• Pertz Lab -- Institute of Cell Biology (ICB)

  A pioneering group at the forefront of real-time control of cellular signaling dynamics using microscopy, quantitative imaging, and optogenetics. This interdisciplinary team collaborates closely with experts in engineering and data science.

• Ginsbourger Group -- Institute of Mathematical Statistics and Actuarial Science (IMSV)

  Renowned for its work in Gaussian process modeling, Bayesian optimal design, and machine learning for scientific discovery. The group maintains strong collaborations across mathematics, machine learning, and applied sciences.

You will have the opportunity to move between both labs regularly, enhancing your ability to communicate across disciplines—a vital asset for your future career.

Project Overview

Cells interpret, integrate, and react to dynamic stimuli through complex signaling networks. The Pertz Lab has developed innovative optogenetic tools and fluorescent biosensors that facilitate direct perturbation and measurement of these networks using light. In partnership with the Ginsbourger Group, we aim to develop autonomous "self-driving" microscopes that:

• Build statistical models of biological dynamics in real-time
• Predict the most informative next experiment
• Execute it automatically on living cells

Key methods employed 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 witness mathematical models in action, guiding experiments in real time. The position also includes a small teaching component in Statistics, which comes with an enhanced salary compared to standard PhD funding in Switzerland.

Why Choose Bern?

• Top-ranked Swiss research university
• International community with a 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
• Strong skills in statistical modeling and probability theory
• Experience in coding (Python, R, Julia, Matlab, etc.)
• Motivation to collaborate closely with experimental researchers
• A 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.