Ballester/CRCM/Inserm/Chef d'equipe

Machine Learning for Precision Oncology

This project will address the question of how to leverage clinical data to improve our ability to predict which cancer patients will respond to a drug treatment. The CONSORE project within IPC has completed the structuration of electronic health records from clinical practice. As a result, we now count with a large volume of structured data from the IPC (currently 258,168 patient records). The successful candidate will investigate and implement predictive models exploiting these data resources.

M2 - research project – Benchmarking classification algorithms on high-dimensional data

We are looking for a highly motivated and diligent student to carry out her/his M2 master project in our group. The ideal candidate will be comfortable writing code in Python and/or R, with prior exposure to supervised learning algorithms. Additional background on tumour molecular profiling and/or biomarker discovery will be an advantage. The project will be building upon our recent work on predicting in vivo tumour response to cancer treatments (https://www.biorxiv.org/content/early/2018/12/04/277772).

M2 - research project - Machine-learning scoring functions for structure-based virtual screening

We are looking for a highly motivated and diligent student to carry out her/his M2 master project in our group. The project requires some knowledge of python programming and machine learning. Additional background on chemical informatics and/or structural bioinformatics will be an advantage. The project will be building upon recent work on predicting the binding of small molecules to proteins with applications to structure-based drug design (https://www.nature.com/articles/srep46710).