Automatic reconstruction of Drosophila average embryonic development at the single-cell scale

Position

Ph.D. Student/Postdoc

Published Date

16 janv. 2021

Until filled

Application

poster

Application deadline

Keywords

Computer Science, Image Analysis, Big-data, Developmental Biology, Drosophila Embryogenesis

The role

We are seeking a highly motivated candidate strongly interested in interdisciplinary science, to join our group and work on a project at the crossroad between Computer Science and Developmental Biology.


The project aims at developing computational methods and models to better understand how robustness to biological noise is achieved during the development of Drosophilaembryos. This will be done by first quantifying and characterising Drosophila embryogenesis variability at the single cell scale.


The successful candidate will be tasked to build statistical representations of the morphogenesis of Drosophila embryos at the single cell scale by combining image analysis, big-data science and data visualisation. To this end, the candidate will first develop novel image and big-data analysis algorithms. These algorithms will be first applied to 3D movies of Drosophila embryos acquired with state-of-the-art light-sheet fluorescence microscopes. The successful candidate will then develop novel algorithms to combine the set of recorded embryos together to build a single-cell scale, in-toto, atlas of Drosophila embryogenesis.


Depending on the advancement of the project and the candidate preferences, the second part of the project will then focus around either integrating complementary single-cell omic data to the atlas or developing machine-learning based methods to analyse, detect and classify cell patterns in the developing embryo.

The role

We are seeking a highly motivated candidate strongly interested in interdisciplinary science, to join our group and work on a project at the crossroad between Computer Science and Developmental Biology.


The project aims at developing computational methods and models to better understand how robustness to biological noise is achieved during the development of Drosophilaembryos. This will be done by first quantifying and characterising Drosophila embryogenesis variability at the single cell scale.


The successful candidate will be tasked to build statistical representations of the morphogenesis of Drosophila embryos at the single cell scale by combining image analysis, big-data science and data visualisation. To this end, the candidate will first develop novel image and big-data analysis algorithms. These algorithms will be first applied to 3D movies of Drosophila embryos acquired with state-of-the-art light-sheet fluorescence microscopes. The successful candidate will then develop novel algorithms to combine the set of recorded embryos together to build a single-cell scale, in-toto, atlas of Drosophila embryogenesis.


Depending on the advancement of the project and the candidate preferences, the second part of the project will then focus around either integrating complementary single-cell omic data to the atlas or developing machine-learning based methods to analyse, detect and classify cell patterns in the developing embryo.

Requirements

Required experience

The candidate must have at least one of the following experience

  • Computer Science: Image Analysis, Graph Theory, Data Science, ...

  • Developmental Biology (sole experience in Developmental Biology requires to be able to show good coding skills)

Desirable experience

  • Basic knowledge in developing in Python

  • Basic knowledge in data structure theory

  • Basic knowledge in Unix

Education and training

  • You hold a master degree/Ph.D in Bioinformatics, Computer Science, Developmental Biology (with good computational skills) or equivalent

Competences

  • You are eager to learn

  • You are creative

  • You have good communication skills

  • You want to work as part of a collaborative team

The offer

  • Contract duration: PhD: 3-year position, Postdoc: 2-year position with possible renewal

  • Target start date: from July 2021 until the position is filled

  • The salary will be based on Aix-Marseille University’s salary scale, depending on the candidate’s profile and experience

Application procedure

All applications must include:

  1. A motivation letter addressed to Léo Guignard.

  2. A complete CV including contact details.

  3. Contact details of at least one (for Ph.D. candidates) or two (for postdoc candidates) referee(s).

All applications must be sent to Léo Guignard by email with the mention [Job-2021] in the title at the address leo.guignard+lab@gmail.com.

Selection process and calendar

The positions will stay opened until filled.

  • Pre-selection: The pre-selection process will be based on qualifications and expertise reflected on the candidates CV and motivation letter. It will be merit-based. All candidates will be informed whether they have been pre-selected or not.

  • Interview: Pre-selected candidates will be contacted to coordinate a set of interviews with a set of selected members of CENTURI (including Léo) and a seminar. The interview will include a computational skill test (no specific coding language is required).

Location

Léo Guignard lab