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PhD thesis in machine learning methods development for cryo-EM image analysis in structural biology

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Français - Anglais

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General information

Reference : UMR7590-SLAJON-001
Workplace : PARIS 05
Date of publication : Monday, September 02, 2019
Scientific Responsible name : Slavica JONIC
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 November 2019
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

This PhD thesis will be focused on the development of machine learning methods for cryo-electron microscopy image analysis. These methods should allow studying continuous conformational variability of biomolecular complexes (https://doi.org/10.1016/j.sbi.2016.12.011). Supervised and non-supervised machine learning methods will be explored in this context. In the supervised learning case, the learning will be based on the results of a method that combines cryo-electron microscopy image analysis with molecular mechanics simulation, previously developed in the team (https://doi.org/10.1016/j.str.2014.01.004).

Required skills and qualities:
- Strong skills in machine learning and image processing
- Strong programming skills
- Good interpersonal skills
- Good oral and written communication skills
- Creativity
- Interest in data analysis for structural biology

Work Context

The work will be performed in the context of a project funded by the ANR, at the Institut de minéralogie, de physique des matériaux et de cosmochimie (IMPMC-UMR 7590, Sorbonne Université, 75005 Paris). The IMPMC is a joint research unit of the CNRS, the Sorbonne Université, and the Muséum National d'Histoire Naturelle, counting around 200 members. It is a highly pluridisciplinary laboratory, composed of researchers, researchers-teachers, and engineers with different backgrounds (physics, Earth science, biology, chemistry, computer science, etc.). Various experimental and theoretical research topics are studied at the IMPMC, such as elucidation of the structure of materials and macromolecular assemblies, investigation of their dynamic properties, study of interactions between the living world and the mineral world, etc.

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