Ries Lab Postdoc: Deep Learning For Superresolution Microscopy

Postdoc: deep learning for superresolution microscopyThe Ries lab is developing super-resolution microscopy methods for structural cell biology. In a WWTF-funded project we will develop a new deep learning-based approach to reconstruct a movie of a cellular process from tens of thousands of snapshots taken with high-throughput super-resolution microscopy and are looking for a Postdoctoral Researcher with a background in machine learning.
Open since Mar 04, 2024About the positionThe overall aim of the project is to develop a computational approach to reconstruct the structure and dynamics of a cellular process at nanometer resolution from tens of thousands of images measured in fixed cells. We will develop this approach on the example of endocytosis, an essential process by which cells take up molecules, but this method will then be applicable to many other cellular processes. You will have abundant data readily available and work closely together with a biologist in the group who will capture new data on demand, and with a computational scientist from our partner lab, the Lab of Jakob Macke in Tübingen. This project will extend previous work based on maximum likelihood estimation (https://doi.org/10.1038/s******** z ).
 
CandidatesWe are looking for a talented, highly motivated postdoctoral scientist who is excited to develop computational approaches with wide applicability in the life sciences. You should hold a PhD degree in computer science or physics and should have a strong background in machine learning, preferably deep learning. Experience in computer vision or image analysis, especially microscopy images, is highly appreciated. Training and supervision will be provided throughout the project, but we also expect a high level of drive and independence. Excellent spoken and written English skills are required.
 
ApplicationPlease send your documents to ******** and include a concise description of research experience, a list of published articles and contact details for three references.
Interviews will be held on a rolling basis and as soon as a suitable candidate is found, the position will be filled. The position is initially funded for a period of three years.

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