Mots-Clés

Biostatistique Data integration Multi-omics Cancer Missing data Deconvolution Clustering.

Description

Postdoc position (2 years) : Identification of the clonal composition of a tumor from panel-sequencing data.

Keywords : Data integration; Multi-omics; Cancer; Missing data; Deconvolution; Clustering.

Aim : To develop a statistical approach to identify the clonal composition of the tumor from panel-sequencing data.

Missions
- The postdoctoral researcher will be part of the ANR Identhic, which focuses on reconstructing the evolutionary history of tumors based on partial sequencing data.
- The candidate will collaborate closely with the four principal members of the project team, as well as with master's and doctoral students working on complementary aspects of the project.
- The candidate will be responsible for the methodological development of statistical approaches for identifying subgroups of cells exhibiting homogeneous behavior from sequencing data, first under complete observation conditions, and then with partial observation.

Activities
- Familiarization with the data, data formatting, and creation of annotations for patient-derived samples.
- Development of a deconvolution method for inferring the clonal composition of samples from sequencing data under complete observation.
- Benchmarking of the method.
- Extension to partial observation sequencing using bio-informed priors, with the development of imputation methods for handling missing data in this context
- Implementation of the methods through efficient algorithms.
- Presentation and discussion of results with consortium members.
- Writing scientific articles to disseminate results to the scientific community.
- Participation in international workshops and conferences.

Skills
- PhD in Biostatistics or Bioinformatics
- Strong interest in programming, particularly proficiency in R or Python
- Prior experience with at least one type of sequencing data

How to apply
- The postdoc position should be filled as soon as possible.
- You can apply by sending us (Alice Cleynen <alice.cleynen@umontpellier.fr>, Sophie Lèbre <sophie.lebre@umontpellier.fr>) a CV and a motivation letter.
- Do not hesitate to contact us directly for more information on the position.