Bioimage analysis

Bioimage analysis

Our group develops bioimage analysis tools that blend continuous mathematical models and computer vision (e.g., learning-based) algorithms.

We are interested in flexible contour representations that allow identifying and precisely characterizing biological objects in a large variety of image data. These models can then be applied to quantify phenotypical variations at the single-cell or single-individual level in experiments ranging from genome-wide knockout screens to population dynamics studies.

We are recruiting students who have a good background in computer vision and image processing, with interests in optimisation, approximation and sampling theory.

Our group will start at EMBL-EBI on 15 September 2018.

Selected publications

Uhlmann V, Ramdya P, Delgado-Gonzalo R, Benton R, Unser M (2017) FlyLimbTracker: An active contour based approach for leg segment tracking in unmarked, freely behaving Drosophila. PLOS ONE 12:1-21.

Uhlmann V, Fageot J, Unser M (2016) Hermite snakes with control of tangents. IEEE Transactions on Image Processing 25:2803-2816.

Delgado-Gonzalo R, Uhlmann V, Schmitter D, Unser M (2015) Snakes on a plane: A perfect snap for bioimage analysis. IEEE Signal Processing Magazine 32:41-48.

Uhlmann V, Haubold C, Hamprecht FA, Unser M (2018) DiversePathsJ: Diverse shortest paths for bioimage analysis. Bioinformatics 34:538–540.

EMBL Interdisciplinary Postdoctoral Fellowships (EI3POD)

Our group is participating in the 2018 EI3POD call for fellowship applications. The EI3POD programme offers an opportunity for fellows to carry out interdisiplinary research in the context of inter-institutional or inter-sectorial collaborations. In this round, we would like to highlight our collaborations with the following groups and topics:

If you would like to pursue an EI3POD fellowship, contact me to discuss your research proposal.

To apply please submit a research proposal and CV, with two referees, through our online proposal. 

Apply online