Anglia Ruskin University ARU Featured PhD Programmes
European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes

Modeling gene regulation using an interpretable variational autoencoder on single-cell genomic data


Development and Stem Cells Department

Strasbourg France Machine Learning Mathematical Modelling

About the Project

Biology is going through an incredible revolution: current experimental techniques allows us to generate GBs of data in each experiment. For instance, the Human Cell Atlas Project aims to map and characterize all cells types in the human body using single-cell genomic techniques as a basis for both understanding human health and disease. This goal represents new exciting challenges in computational biology as novel approaches are required to identify patterns, extract valuable information and produce reliable predictions. machine and deep learning techniques have been proven to be a very powerful tools for these tasks. However, the black-box nature of these methods hinders the interpretability of the latent variables. In this project we aim to develop an interpretable variational autoencoder to model gene regulation from single-cell transcriptomic data. Ultimately, we envision that the outcome of this research will aid the development of new cell therapies.

About you

You should hold a M.Sc. degree in computational biology, machine learning, data science, artificial intelligence, or similar by September 2021. Proven experience developing and applying machine and deep learning tools is expected for the first project and experience analyzing genomic data for the second. Prior knowledge in biology is not required. A strong motivation and a good capacity to work in a multidisciplinary team are also important. English is the communication language in the team.

About us

We are a highly interdisciplinary team focusing on building computational and biophysical models of gene regulation by integrating single-cell imaging and sequencing data. We used principle-based methods rooted in machine learning, Bayesian statistics and biophysics. The IGBMC offers an exceptional computational and experimental infrastructure that allow us to develop our models and test them experimentally. 

The IGBMC is one of the leading biomedical research centres in Europe bringing together more than 700 researchers, PhD students and scientific staff grouped in 50 research teams and over a dozen of scientific platforms and core facilities. The IGBMC is dedicated to fundamental and applied research in life sciences, ranging from structural biology to human genetics, regulation of gene expression, biophysics and stem cells.

Applications

To apply, send a single pdf file with your CV, a cover letter describing how your expertise and experience fit in the project and the contact information of at least two references. Applications will be considered until 31/05/2021.

Contact

Nacho Molina – http://www.igbmc.fr/molina/


Funding Notes

ANR funding

References

1) Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning: https://www.biorxiv.org/content/10.1101/2021.03.17.435887v1
2) Regulation of transcription reactivation dynamics exiting mitosis: https://www.biorxiv.org/content/10.1101/2020.04.15.042853v1

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here

The information you submit to IGBMC, Strasbourg will only be used by them or their data partners to deal with your enquiry, according to their privacy notice. For more information on how we use and store your data, please read our privacy statement.

* required field

Your enquiry has been emailed successfully



Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2021
All rights reserved.