Context and Subject:
Our laboratories are involved in cancer fight through the identification of key genes acting in the oncogenic process. To that end both laboratories have developed an original RNAi-based screening approach using cell microarrays. Briefly, it consists in high throughput and high content screening on microarrays, of the phenotypic consequences of gene depletion at single cell level. A functional screen implies the generation of data containing millions of lines, corresponding to each cell information. The thesis work is to develop dedicated data analysis, sharing its time between the two laboratories, and also in strong collaboration with the University of Turku and the Centre for Computational Biology of Mines ParisTech (CBIO).
This PhD in bioinformatics (lasting typically 3 years), close to biologists/experimentalists, includes data analysis, experimental modelization, hits discovery (genes of interest in carcinogenesis) together with system biology of cancer cells. In particular, experimental results from both teams will be compared to data base in order to extract global behaviour of gene family on cell proliferation. Data processing, implying the use and development of state-of-the art statistical models, dimension reduction and clustering algorithms facilitating meaningful data representation, will be mainly done using the R software for statistical computing.
Two main subjects are of particular interest for both team, and one of each will be fully investigated by the successful candidate. The first subject consists in better evaluation of the false positive hits based on machine learning methods. Different learning algorithms could then be tested and new designed algorithms will be developed for the purpose.
The second project is image and data analyses of prostatic 3D cultures (which is also of great interest for both labs). Based on the software already developed at VTT, it will consist in the optimisation of all metrics used to characterize these 3D structures (already 26 parameters analyzed at VTT).
The PhD student will share its time equally between the CEA (Grenoble, France) and the VTT (Turku, Finland).
Background of the student:
Statistics or applied mathematics, interested in biological and health application. Knowledge of R would be a plus.
Applicant must own a Master in statistics, mathematics, computing or related. Applications must be submitted as one pdf file containing all materials. To apply, send an email to Laurent Guyon, and attach the following materials in English:
- A letter motivating the application (cover letter, max 1 page)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma