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Application Deadline
01
Jul 2019
2019-07-01 8:00:00 2019-07-01 18:00:00 Europe/Paris Post-Doctoral/Research Engineer: 3D Segmentation in virtual reality with Bayesian learning Description The DIVA (Data Integration and Visualization in Virtual and Augmented Environments) project aims to create environments for data treatment that leverages virtual reality (VR), human-data interaction and automated algorithms. It is a joint […] "25-28 rue du Dr. Roux, 75015, Paris" Jean-Baptiste Masson jean-baptiste.masson@pasteur.fr

Description

The DIVA (Data Integration and Visualization in Virtual and Augmented Environments) project aims to create environments for data treatment that leverages virtual reality (VR), human-data interaction and automated algorithms. It is a joint initiative between the Institut Pasteur and the Institut Curie. The proposed post-doctoral/research engineer fellowship involves developing machine-aided segmentation approaches to volumetric imaging data. Key to our segmentation approach is the relation between user intervention and data treatment. It is tailored to handle data in limited quantities, possibly very noisy, and to allow rapid and robust learning of the required procedures to extract relevant information from data.

Development of the proposed segmentation tool will be based on an in-house software platform that is designed to load microscopy image into VR environments. The platform generates entire scenes allowing real-time interaction with data (i.e. representation modifications, annotations and projections of data). Currently the platform is available in alpha version at both DIVA host institutes.

More information on applications of the DIVA project is available here.

We are proposing a two years contract financed by the DIM ELICIT program for a motivated candidate. They will be expected to contribute to our efforts of designing segmentation procedures for noisy data coming from microscopy images. The successful candidate will employ Bayesian pixel feature learning couple to VR live data tagging to segment the images. Strong experience in programming is required. The approach will be tested on large-scale multimodal images of neurons. The successful candidate will be working directly with the engineer team developing the DIVA Platform headed by Mohamed El Beheiry. She/He will also work directly with Kurt Sailor and Marina Alonso from Lledo’s lab to investigate the neural architecture of subsets of mice neurons at the full brain scale.

Figure 1: Demonstration of DIVA on confocal data with an example of raw data below.

The successful candidate will join a highly multidisciplinary lab of physicists and computer scientists who use computational approaches to study random walks of biomolecules in living cells and study the relationship between neural architecture and behavior in drosophila larva. Localized in the world-renowned Institut Pasteur, the successful candidate will have privileged access to multiple GPU clusters and custom platforms in the lab.

Required Skills

  • C, C++ or C#
  • Scripting (e.g. Python, Bash)
  • Statistical Physics
  • Inference and Numerical Optimization

Recommended Skills

  • Image Processing
  • Machine Learning Frameworks (e.g. PyTorch, TensorFlow)
  • Computer Graphics (e.g. OpenGL, GLSL)
  • General-Purpose GPU Programming (e.g. CUDA, OpenCL)

Duration

2 years

Localization

Institut Pasteur (Paris, France)

Contact Information

Interested candidates should contact Jean-Baptiste Masson (jbmasson@pasteur.fr) with their CV, a brief motivation letter and two letters of recommendation.