PhD Position in Statistics with a focus on Statistical Machine Learning for Self-Driving Microscopy
Mehr als 30 Tage altAngaben zum Job
| Firma | Universität Bern |
| Kategorie | Forschung / Wissenschaft, Öffentliche Verwaltung | Pensum | 100% |
| Lohn (geschätzt) | CHF 88'000 – 112'000 / Jahr |
| Einsatzort | Bern |
Job-Inhalt
Joint project between – Pertz Lab (Institute of Cell Biology) & D. Ginsbourger's Group (Institute of Mathematical Statistics & Actuarial Science)
We are seeking highly qualified, motivated and creative candidates wishing to join a collaborative project at the interface of statistical machine learning and live-cell biology.
The PhD in statistics will be co-supervised by Prof. David Ginsbourger (Statistics) and
Prof. Olivier Pertz (Cell Biology), and the student will be equally embedded in both research environments.
Your Environment
This project provides a rare opportunity to see statistical machine learning models come alive, guiding live experiments. The recruited PhD student will evolve between both groups 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. D. Ginsbourger's group is Internationally recognized in Gaussian process modeling, Bayesian optimal design, and statistical data science for the sciences. Together, 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
Your Profile
Application
Please submit your application only electronically in a single PDF with the following documents:
- short motivation letter (max. 1 page)
- 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
[email protected]
Please prefer applying with an email rather than through the application button.
Applications will be reviewed on a rolling basis until the position is filled.