PhD position in Statistical Machine Learning for Self-Driving Microscopy

vor 1 Woche

Bern, Bern, Schweiz Kanton Bern Vollzeit

**PhD position in Statistical Machine Learning for Self-Driving Microscopy

100%**
Joint position – Pertz Lab ( Institute of Cell Biology ) & Ginsbourger Group ( Institute of Mathematical Statistics & Actuarial Science )

We are recruiting a highly motivated PhD student to join a fully collaborative doctoral project at the interface of machine learning, statistics, and live-cell biology.

The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally embedded in both research environments.

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. Interdisciplinary team with close ties to engineering and data science.

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

Internationally recognized in Gaussian process modeling, Bayesian optimal design, and machine learning for scientific discovery. Strong collaborations across mathematics, ML, and applied sciences.

You will move between both labs regularly and become fluent in communicating across disciplines - a major career asset.

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 allow direct perturbation and measurement of these networks using light. Together 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 it automatically on living cells

Key Methods 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 provides a rare opportunity to see mathematical models come alive, guiding experiments as they happen.

Teaching: The position includes a small teaching duty in Statistics → includes enhanced salary compared to standard PhD funding in Switzerland.

Why choosing Bern?

  • Top-ranked Swiss research university
  • International community, high quality of life
  • Easy access to Europe
  • Outstanding support for early-career researchers

Your Profile

  • Master's degree in Mathematics, Statistics, Computer Science, Engineering
  • Solid skills in statistical modeling & probability theory
  • Experience in coding (Python, R, Julia, Matlab...)
  • Motivation to work closely with experimental researchers
  • Curiosity about biological systems - no prior wet-lab experience needed

Application
Please submit your application only electronically in a single PDF with the following documents:

  • short motivation letter
  • CV including month/year
  • BSc and MSc transcripts (in one of Switzerland's official languages, or English) of scores
  • Contact information for two references
  • Any other relevant document

In One Email To Both Addresses

Applications will be reviewed on a rolling basis until the position is filled.

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